EDA_chest_xray.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "from scipy.stats import norm\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy import stats\n",
    "from scipy.stats import norm, skew \n",
    "from scipy.special import boxcox1p\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = 'all'\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load pneumonia_train data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "pne_train = pd.read_csv('pneumonia_train_small.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = pne_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "nor_train = pd.read_csv('normal_train_small.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "pne_train['label'] = 1\n",
    "nor_train['label'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.concat([pne_train, nor_train], ignore_index=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = train.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = train[columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
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       "      <th>gray_13</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>gray_15</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>r_lungsize</th>\n",
       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
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       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "      <td>5213.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7271.844044</td>\n",
       "      <td>4137.315174</td>\n",
       "      <td>4122.491272</td>\n",
       "      <td>4128.920583</td>\n",
       "      <td>4138.458086</td>\n",
       "      <td>4143.173604</td>\n",
       "      <td>4143.589871</td>\n",
       "      <td>4141.932477</td>\n",
       "      <td>4136.913677</td>\n",
       "      <td>4128.765778</td>\n",
       "      <td>...</td>\n",
       "      <td>4132.081143</td>\n",
       "      <td>4148.666603</td>\n",
       "      <td>4206.272204</td>\n",
       "      <td>4412.591982</td>\n",
       "      <td>16.830424</td>\n",
       "      <td>439356.733167</td>\n",
       "      <td>5.311875</td>\n",
       "      <td>9842.565701</td>\n",
       "      <td>6107.836754</td>\n",
       "      <td>0.636907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3280.789928</td>\n",
       "      <td>322.555303</td>\n",
       "      <td>268.674483</td>\n",
       "      <td>236.080411</td>\n",
       "      <td>233.167553</td>\n",
       "      <td>234.065188</td>\n",
       "      <td>235.302662</td>\n",
       "      <td>235.078084</td>\n",
       "      <td>235.203778</td>\n",
       "      <td>233.609778</td>\n",
       "      <td>...</td>\n",
       "      <td>231.273948</td>\n",
       "      <td>243.347879</td>\n",
       "      <td>267.270882</td>\n",
       "      <td>341.497591</td>\n",
       "      <td>70.821487</td>\n",
       "      <td>24826.706554</td>\n",
       "      <td>1.045582</td>\n",
       "      <td>2034.509667</td>\n",
       "      <td>2296.288113</td>\n",
       "      <td>0.254305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1418.000000</td>\n",
       "      <td>188.000000</td>\n",
       "      <td>2365.000000</td>\n",
       "      <td>2574.000000</td>\n",
       "      <td>2929.000000</td>\n",
       "      <td>2921.000000</td>\n",
       "      <td>2949.000000</td>\n",
       "      <td>2901.000000</td>\n",
       "      <td>2965.000000</td>\n",
       "      <td>2901.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2751.000000</td>\n",
       "      <td>1876.000000</td>\n",
       "      <td>1610.000000</td>\n",
       "      <td>1517.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>310385.000000</td>\n",
       "      <td>2.408069</td>\n",
       "      <td>1574.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4366.000000</td>\n",
       "      <td>3941.000000</td>\n",
       "      <td>3953.000000</td>\n",
       "      <td>3968.000000</td>\n",
       "      <td>3975.000000</td>\n",
       "      <td>3980.000000</td>\n",
       "      <td>3980.000000</td>\n",
       "      <td>3981.000000</td>\n",
       "      <td>3975.000000</td>\n",
       "      <td>3968.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3977.000000</td>\n",
       "      <td>3987.000000</td>\n",
       "      <td>4022.000000</td>\n",
       "      <td>4163.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>421565.000000</td>\n",
       "      <td>4.531461</td>\n",
       "      <td>8609.000000</td>\n",
       "      <td>4765.000000</td>\n",
       "      <td>0.511000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6157.000000</td>\n",
       "      <td>4166.000000</td>\n",
       "      <td>4181.000000</td>\n",
       "      <td>4199.000000</td>\n",
       "      <td>4212.000000</td>\n",
       "      <td>4217.000000</td>\n",
       "      <td>4213.000000</td>\n",
       "      <td>4212.000000</td>\n",
       "      <td>4202.000000</td>\n",
       "      <td>4192.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4187.000000</td>\n",
       "      <td>4193.000000</td>\n",
       "      <td>4244.000000</td>\n",
       "      <td>4464.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>447780.000000</td>\n",
       "      <td>5.143827</td>\n",
       "      <td>9755.000000</td>\n",
       "      <td>6251.000000</td>\n",
       "      <td>0.656000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9624.000000</td>\n",
       "      <td>4313.000000</td>\n",
       "      <td>4304.000000</td>\n",
       "      <td>4319.000000</td>\n",
       "      <td>4332.000000</td>\n",
       "      <td>4341.000000</td>\n",
       "      <td>4343.000000</td>\n",
       "      <td>4339.000000</td>\n",
       "      <td>4335.000000</td>\n",
       "      <td>4323.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4317.000000</td>\n",
       "      <td>4335.000000</td>\n",
       "      <td>4401.000000</td>\n",
       "      <td>4651.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>461415.000000</td>\n",
       "      <td>6.020274</td>\n",
       "      <td>10964.000000</td>\n",
       "      <td>7571.000000</td>\n",
       "      <td>0.761000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>24349.000000</td>\n",
       "      <td>9053.000000</td>\n",
       "      <td>8180.000000</td>\n",
       "      <td>5218.000000</td>\n",
       "      <td>4653.000000</td>\n",
       "      <td>4559.000000</td>\n",
       "      <td>4597.000000</td>\n",
       "      <td>4887.000000</td>\n",
       "      <td>4863.000000</td>\n",
       "      <td>4655.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4905.000000</td>\n",
       "      <td>5986.000000</td>\n",
       "      <td>5457.000000</td>\n",
       "      <td>9006.000000</td>\n",
       "      <td>2958.000000</td>\n",
       "      <td>470132.000000</td>\n",
       "      <td>9.463284</td>\n",
       "      <td>24615.000000</td>\n",
       "      <td>15891.000000</td>\n",
       "      <td>3.060000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0       gray_1       gray_2       gray_3       gray_4  \\\n",
       "count   5213.000000  5213.000000  5213.000000  5213.000000  5213.000000   \n",
       "mean    7271.844044  4137.315174  4122.491272  4128.920583  4138.458086   \n",
       "std     3280.789928   322.555303   268.674483   236.080411   233.167553   \n",
       "min     1418.000000   188.000000  2365.000000  2574.000000  2929.000000   \n",
       "25%     4366.000000  3941.000000  3953.000000  3968.000000  3975.000000   \n",
       "50%     6157.000000  4166.000000  4181.000000  4199.000000  4212.000000   \n",
       "75%     9624.000000  4313.000000  4304.000000  4319.000000  4332.000000   \n",
       "max    24349.000000  9053.000000  8180.000000  5218.000000  4653.000000   \n",
       "\n",
       "            gray_5       gray_6       gray_7       gray_8       gray_9  \\\n",
       "count  5213.000000  5213.000000  5213.000000  5213.000000  5213.000000   \n",
       "mean   4143.173604  4143.589871  4141.932477  4136.913677  4128.765778   \n",
       "std     234.065188   235.302662   235.078084   235.203778   233.609778   \n",
       "min    2921.000000  2949.000000  2901.000000  2965.000000  2901.000000   \n",
       "25%    3980.000000  3980.000000  3981.000000  3975.000000  3968.000000   \n",
       "50%    4217.000000  4213.000000  4212.000000  4202.000000  4192.000000   \n",
       "75%    4341.000000  4343.000000  4339.000000  4335.000000  4323.000000   \n",
       "max    4559.000000  4597.000000  4887.000000  4863.000000  4655.000000   \n",
       "\n",
       "          ...           gray_11      gray_12      gray_13      gray_14  \\\n",
       "count     ...       5213.000000  5213.000000  5213.000000  5213.000000   \n",
       "mean      ...       4132.081143  4148.666603  4206.272204  4412.591982   \n",
       "std       ...        231.273948   243.347879   267.270882   341.497591   \n",
       "min       ...       2751.000000  1876.000000  1610.000000  1517.000000   \n",
       "25%       ...       3977.000000  3987.000000  4022.000000  4163.000000   \n",
       "50%       ...       4187.000000  4193.000000  4244.000000  4464.000000   \n",
       "75%       ...       4317.000000  4335.000000  4401.000000  4651.000000   \n",
       "max       ...       4905.000000  5986.000000  5457.000000  9006.000000   \n",
       "\n",
       "           gray_15     total_gray  lung_density    r_lungsize    l_lungsize  \\\n",
       "count  5213.000000    5213.000000   5213.000000   5213.000000   5213.000000   \n",
       "mean     16.830424  439356.733167      5.311875   9842.565701   6107.836754   \n",
       "std      70.821487   24826.706554      1.045582   2034.509667   2296.288113   \n",
       "min       1.000000  310385.000000      2.408069   1574.000000      0.000000   \n",
       "25%       3.000000  421565.000000      4.531461   8609.000000   4765.000000   \n",
       "50%       7.000000  447780.000000      5.143827   9755.000000   6251.000000   \n",
       "75%      18.000000  461415.000000      6.020274  10964.000000   7571.000000   \n",
       "max    2958.000000  470132.000000      9.463284  24615.000000  15891.000000   \n",
       "\n",
       "          fraction  \n",
       "count  5213.000000  \n",
       "mean      0.636907  \n",
       "std       0.254305  \n",
       "min       0.000000  \n",
       "25%       0.511000  \n",
       "50%       0.656000  \n",
       "75%       0.761000  \n",
       "max       3.060000  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:2: DataConversionWarning: Data with input dtype int64, float64 were all converted to float64 by the scale function.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "#center the variables\n",
    "train_centered = preprocessing.scale(df, with_mean='True', with_std='False')\n",
    "#convert back into a Pandas dataframe and add column names\n",
    "train_centered_df = pd.DataFrame(train_centered, columns=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
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       "      <th>gray_0</th>\n",
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       "      <th>lung_density</th>\n",
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       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-1.441820e-16</td>\n",
       "      <td>8.281203e-16</td>\n",
       "      <td>1.482157e-15</td>\n",
       "      <td>-1.028229e-16</td>\n",
       "      <td>1.150965e-15</td>\n",
       "      <td>-4.119730e-16</td>\n",
       "      <td>-4.651521e-16</td>\n",
       "      <td>1.969991e-17</td>\n",
       "      <td>-1.521813e-15</td>\n",
       "      <td>5.503835e-16</td>\n",
       "      <td>...</td>\n",
       "      <td>4.208753e-16</td>\n",
       "      <td>1.486630e-15</td>\n",
       "      <td>-3.969798e-16</td>\n",
       "      <td>5.587480e-16</td>\n",
       "      <td>-4.685091e-16</td>\n",
       "      <td>-7.715550e-16</td>\n",
       "      <td>-8.016565e-18</td>\n",
       "      <td>2.355470e-16</td>\n",
       "      <td>8.109974e-17</td>\n",
       "      <td>4.414910e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.784450e+00</td>\n",
       "      <td>-1.224501e+01</td>\n",
       "      <td>-6.541968e+00</td>\n",
       "      <td>-6.587034e+00</td>\n",
       "      <td>-5.187575e+00</td>\n",
       "      <td>-5.222010e+00</td>\n",
       "      <td>-5.077310e+00</td>\n",
       "      <td>-5.279316e+00</td>\n",
       "      <td>-4.983024e+00</td>\n",
       "      <td>-5.256131e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.972197e+00</td>\n",
       "      <td>-9.340063e+00</td>\n",
       "      <td>-9.714943e+00</td>\n",
       "      <td>-8.479913e+00</td>\n",
       "      <td>-2.235472e-01</td>\n",
       "      <td>-5.195377e+00</td>\n",
       "      <td>-2.777481e+00</td>\n",
       "      <td>-4.064546e+00</td>\n",
       "      <td>-2.660129e+00</td>\n",
       "      <td>-2.504743e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-8.857997e-01</td>\n",
       "      <td>-6.086832e-01</td>\n",
       "      <td>-6.309030e-01</td>\n",
       "      <td>-6.817000e-01</td>\n",
       "      <td>-7.011000e-01</td>\n",
       "      <td>-6.971958e-01</td>\n",
       "      <td>-6.952984e-01</td>\n",
       "      <td>-6.846572e-01</td>\n",
       "      <td>-6.884635e-01</td>\n",
       "      <td>-6.882469e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.706160e-01</td>\n",
       "      <td>-6.644073e-01</td>\n",
       "      <td>-6.895247e-01</td>\n",
       "      <td>-7.309449e-01</td>\n",
       "      <td>-1.953044e-01</td>\n",
       "      <td>-7.167056e-01</td>\n",
       "      <td>-7.464640e-01</td>\n",
       "      <td>-6.063790e-01</td>\n",
       "      <td>-5.848419e-01</td>\n",
       "      <td>-4.951508e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-3.398422e-01</td>\n",
       "      <td>8.893848e-02</td>\n",
       "      <td>2.177890e-01</td>\n",
       "      <td>2.968740e-01</td>\n",
       "      <td>3.154340e-01</td>\n",
       "      <td>3.154398e-01</td>\n",
       "      <td>2.950106e-01</td>\n",
       "      <td>2.980892e-01</td>\n",
       "      <td>2.767497e-01</td>\n",
       "      <td>2.707091e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.374851e-01</td>\n",
       "      <td>1.821986e-01</td>\n",
       "      <td>1.411729e-01</td>\n",
       "      <td>1.505514e-01</td>\n",
       "      <td>-1.388190e-01</td>\n",
       "      <td>3.393150e-01</td>\n",
       "      <td>-1.607381e-01</td>\n",
       "      <td>-4.304433e-02</td>\n",
       "      <td>6.235149e-02</td>\n",
       "      <td>7.508578e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.170168e-01</td>\n",
       "      <td>5.447180e-01</td>\n",
       "      <td>6.756360e-01</td>\n",
       "      <td>8.052242e-01</td>\n",
       "      <td>8.301347e-01</td>\n",
       "      <td>8.452576e-01</td>\n",
       "      <td>8.475436e-01</td>\n",
       "      <td>8.383871e-01</td>\n",
       "      <td>8.422710e-01</td>\n",
       "      <td>8.315271e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>7.996430e-01</td>\n",
       "      <td>7.657814e-01</td>\n",
       "      <td>7.286483e-01</td>\n",
       "      <td>6.981920e-01</td>\n",
       "      <td>1.651601e-02</td>\n",
       "      <td>8.885747e-01</td>\n",
       "      <td>6.775806e-01</td>\n",
       "      <td>5.512591e-01</td>\n",
       "      <td>6.372474e-01</td>\n",
       "      <td>4.880157e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.205696e+00</td>\n",
       "      <td>1.524128e+01</td>\n",
       "      <td>1.510340e+01</td>\n",
       "      <td>4.613614e+00</td>\n",
       "      <td>2.206959e+00</td>\n",
       "      <td>1.776711e+00</td>\n",
       "      <td>1.927108e+00</td>\n",
       "      <td>3.169751e+00</td>\n",
       "      <td>3.087348e+00</td>\n",
       "      <td>2.252837e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>3.342326e+00</td>\n",
       "      <td>7.550958e+00</td>\n",
       "      <td>4.680075e+00</td>\n",
       "      <td>1.345207e+01</td>\n",
       "      <td>4.153332e+01</td>\n",
       "      <td>1.239722e+00</td>\n",
       "      <td>3.970808e+00</td>\n",
       "      <td>7.261628e+00</td>\n",
       "      <td>4.260834e+00</td>\n",
       "      <td>9.529214e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0        gray_1        gray_2        gray_3        gray_4  \\\n",
       "count  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03   \n",
       "mean  -1.441820e-16  8.281203e-16  1.482157e-15 -1.028229e-16  1.150965e-15   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -1.784450e+00 -1.224501e+01 -6.541968e+00 -6.587034e+00 -5.187575e+00   \n",
       "25%   -8.857997e-01 -6.086832e-01 -6.309030e-01 -6.817000e-01 -7.011000e-01   \n",
       "50%   -3.398422e-01  8.893848e-02  2.177890e-01  2.968740e-01  3.154340e-01   \n",
       "75%    7.170168e-01  5.447180e-01  6.756360e-01  8.052242e-01  8.301347e-01   \n",
       "max    5.205696e+00  1.524128e+01  1.510340e+01  4.613614e+00  2.206959e+00   \n",
       "\n",
       "             gray_5        gray_6        gray_7        gray_8        gray_9  \\\n",
       "count  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03   \n",
       "mean  -4.119730e-16 -4.651521e-16  1.969991e-17 -1.521813e-15  5.503835e-16   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -5.222010e+00 -5.077310e+00 -5.279316e+00 -4.983024e+00 -5.256131e+00   \n",
       "25%   -6.971958e-01 -6.952984e-01 -6.846572e-01 -6.884635e-01 -6.882469e-01   \n",
       "50%    3.154398e-01  2.950106e-01  2.980892e-01  2.767497e-01  2.707091e-01   \n",
       "75%    8.452576e-01  8.475436e-01  8.383871e-01  8.422710e-01  8.315271e-01   \n",
       "max    1.776711e+00  1.927108e+00  3.169751e+00  3.087348e+00  2.252837e+00   \n",
       "\n",
       "           ...            gray_11       gray_12       gray_13       gray_14  \\\n",
       "count      ...       5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03   \n",
       "mean       ...       4.208753e-16  1.486630e-15 -3.969798e-16  5.587480e-16   \n",
       "std        ...       1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min        ...      -5.972197e+00 -9.340063e+00 -9.714943e+00 -8.479913e+00   \n",
       "25%        ...      -6.706160e-01 -6.644073e-01 -6.895247e-01 -7.309449e-01   \n",
       "50%        ...       2.374851e-01  1.821986e-01  1.411729e-01  1.505514e-01   \n",
       "75%        ...       7.996430e-01  7.657814e-01  7.286483e-01  6.981920e-01   \n",
       "max        ...       3.342326e+00  7.550958e+00  4.680075e+00  1.345207e+01   \n",
       "\n",
       "            gray_15    total_gray  lung_density    r_lungsize    l_lungsize  \\\n",
       "count  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03  5.213000e+03   \n",
       "mean  -4.685091e-16 -7.715550e-16 -8.016565e-18  2.355470e-16  8.109974e-17   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -2.235472e-01 -5.195377e+00 -2.777481e+00 -4.064546e+00 -2.660129e+00   \n",
       "25%   -1.953044e-01 -7.167056e-01 -7.464640e-01 -6.063790e-01 -5.848419e-01   \n",
       "50%   -1.388190e-01  3.393150e-01 -1.607381e-01 -4.304433e-02  6.235149e-02   \n",
       "75%    1.651601e-02  8.885747e-01  6.775806e-01  5.512591e-01  6.372474e-01   \n",
       "max    4.153332e+01  1.239722e+00  3.970808e+00  7.261628e+00  4.260834e+00   \n",
       "\n",
       "           fraction  \n",
       "count  5.213000e+03  \n",
       "mean   4.414910e-17  \n",
       "std    1.000096e+00  \n",
       "min   -2.504743e+00  \n",
       "25%   -4.951508e-01  \n",
       "50%    7.508578e-02  \n",
       "75%    4.880157e-01  \n",
       "max    9.529214e+00  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_centered_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add label for this dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gray_0          0\n",
       "gray_1          0\n",
       "gray_2          0\n",
       "gray_3          0\n",
       "gray_4          0\n",
       "gray_5          0\n",
       "gray_6          0\n",
       "gray_7          0\n",
       "gray_8          0\n",
       "gray_9          0\n",
       "gray_10         0\n",
       "gray_11         0\n",
       "gray_12         0\n",
       "gray_13         0\n",
       "gray_14         0\n",
       "gray_15         0\n",
       "total_gray      0\n",
       "lung_density    0\n",
       "r_lungsize      0\n",
       "l_lungsize      0\n",
       "fraction        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_centered_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Try another way to select features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SelectKBest(k=6, score_func=<function f_classif at 0x1a1661e9d8>)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_selection import SelectKBest\n",
    "k_best = SelectKBest(k=6)\n",
    "k_best.fit(train_centered_df, train['label'])\n",
    "scores = k_best.scores_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 713.10589212,  441.55011439,  497.14059706,  590.06693144,\n",
       "        609.98100054,  661.33367682,  694.22770345,  681.08313004,\n",
       "        638.09711764,  532.05688075,  433.59851457,  446.16225397,\n",
       "        552.75830008,  580.6887346 , 1318.21820728,  156.51068345,\n",
       "        748.4382315 , 1092.9658326 ,   56.58787923,   85.64818466,\n",
       "        121.82674645])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores\n",
    "pairs = zip(columns, scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do the same step for normal dataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_centered_df['label'] = train['label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gray_0</th>\n",
       "      <th>gray_1</th>\n",
       "      <th>gray_2</th>\n",
       "      <th>gray_3</th>\n",
       "      <th>gray_4</th>\n",
       "      <th>gray_5</th>\n",
       "      <th>gray_6</th>\n",
       "      <th>gray_7</th>\n",
       "      <th>gray_8</th>\n",
       "      <th>gray_9</th>\n",
       "      <th>...</th>\n",
       "      <th>gray_12</th>\n",
       "      <th>gray_13</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>gray_15</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>r_lungsize</th>\n",
       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5216.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.050493e-16</td>\n",
       "      <td>-9.912827e-16</td>\n",
       "      <td>7.769220e-16</td>\n",
       "      <td>-1.359044e-15</td>\n",
       "      <td>-9.623565e-16</td>\n",
       "      <td>-1.244063e-15</td>\n",
       "      <td>-1.336354e-15</td>\n",
       "      <td>3.890250e-16</td>\n",
       "      <td>-1.633194e-16</td>\n",
       "      <td>1.383139e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>9.279387e-16</td>\n",
       "      <td>7.976535e-16</td>\n",
       "      <td>-1.843974e-15</td>\n",
       "      <td>1.496252e-16</td>\n",
       "      <td>1.259111e-15</td>\n",
       "      <td>-5.339916e-16</td>\n",
       "      <td>3.389416e-16</td>\n",
       "      <td>-1.474196e-16</td>\n",
       "      <td>5.461667e-16</td>\n",
       "      <td>0.742906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>0.437073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.784543e+00</td>\n",
       "      <td>-1.224848e+01</td>\n",
       "      <td>-6.543727e+00</td>\n",
       "      <td>-6.588508e+00</td>\n",
       "      <td>-5.187585e+00</td>\n",
       "      <td>-5.223107e+00</td>\n",
       "      <td>-5.078521e+00</td>\n",
       "      <td>-5.280877e+00</td>\n",
       "      <td>-4.983875e+00</td>\n",
       "      <td>-5.257274e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.337698e+00</td>\n",
       "      <td>-9.710113e+00</td>\n",
       "      <td>-8.481079e+00</td>\n",
       "      <td>-2.234938e-01</td>\n",
       "      <td>-5.196343e+00</td>\n",
       "      <td>-5.042037e+00</td>\n",
       "      <td>-4.804644e+00</td>\n",
       "      <td>-2.653969e+00</td>\n",
       "      <td>-2.504743e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-8.857126e-01</td>\n",
       "      <td>-6.066525e-01</td>\n",
       "      <td>-6.310800e-01</td>\n",
       "      <td>-6.817843e-01</td>\n",
       "      <td>-7.019907e-01</td>\n",
       "      <td>-6.974575e-01</td>\n",
       "      <td>-6.954582e-01</td>\n",
       "      <td>-6.849231e-01</td>\n",
       "      <td>-6.887822e-01</td>\n",
       "      <td>-6.886303e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.647812e-01</td>\n",
       "      <td>-6.901019e-01</td>\n",
       "      <td>-7.313986e-01</td>\n",
       "      <td>-1.952433e-01</td>\n",
       "      <td>-7.167310e-01</td>\n",
       "      <td>-7.394767e-01</td>\n",
       "      <td>-6.012113e-01</td>\n",
       "      <td>-5.832742e-01</td>\n",
       "      <td>-4.951508e-01</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-3.394934e-01</td>\n",
       "      <td>8.883303e-02</td>\n",
       "      <td>2.178390e-01</td>\n",
       "      <td>2.970201e-01</td>\n",
       "      <td>3.156591e-01</td>\n",
       "      <td>3.153649e-01</td>\n",
       "      <td>2.950886e-01</td>\n",
       "      <td>2.959727e-01</td>\n",
       "      <td>2.786769e-01</td>\n",
       "      <td>2.704851e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.815574e-01</td>\n",
       "      <td>1.419679e-01</td>\n",
       "      <td>1.501788e-01</td>\n",
       "      <td>-1.387422e-01</td>\n",
       "      <td>3.391326e-01</td>\n",
       "      <td>-1.570540e-01</td>\n",
       "      <td>-4.049319e-02</td>\n",
       "      <td>6.333544e-02</td>\n",
       "      <td>7.508578e-02</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.169673e-01</td>\n",
       "      <td>5.447366e-01</td>\n",
       "      <td>6.758085e-01</td>\n",
       "      <td>8.054898e-01</td>\n",
       "      <td>8.303819e-01</td>\n",
       "      <td>8.452803e-01</td>\n",
       "      <td>8.477542e-01</td>\n",
       "      <td>8.385507e-01</td>\n",
       "      <td>8.421420e-01</td>\n",
       "      <td>8.313963e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>7.649559e-01</td>\n",
       "      <td>7.272215e-01</td>\n",
       "      <td>6.978698e-01</td>\n",
       "      <td>1.663564e-02</td>\n",
       "      <td>8.882908e-01</td>\n",
       "      <td>6.750585e-01</td>\n",
       "      <td>5.497750e-01</td>\n",
       "      <td>6.370127e-01</td>\n",
       "      <td>4.880157e-01</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.207001e+00</td>\n",
       "      <td>1.524530e+01</td>\n",
       "      <td>1.510743e+01</td>\n",
       "      <td>4.614776e+00</td>\n",
       "      <td>2.207265e+00</td>\n",
       "      <td>1.776906e+00</td>\n",
       "      <td>1.927578e+00</td>\n",
       "      <td>3.170572e+00</td>\n",
       "      <td>3.087497e+00</td>\n",
       "      <td>2.252942e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.547991e+00</td>\n",
       "      <td>4.676281e+00</td>\n",
       "      <td>1.345292e+01</td>\n",
       "      <td>4.154491e+01</td>\n",
       "      <td>1.239456e+00</td>\n",
       "      <td>3.945690e+00</td>\n",
       "      <td>7.218072e+00</td>\n",
       "      <td>4.254940e+00</td>\n",
       "      <td>9.529214e+00</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0        gray_1        gray_2        gray_3        gray_4  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean   5.050493e-16 -9.912827e-16  7.769220e-16 -1.359044e-15 -9.623565e-16   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -1.784543e+00 -1.224848e+01 -6.543727e+00 -6.588508e+00 -5.187585e+00   \n",
       "25%   -8.857126e-01 -6.066525e-01 -6.310800e-01 -6.817843e-01 -7.019907e-01   \n",
       "50%   -3.394934e-01  8.883303e-02  2.178390e-01  2.970201e-01  3.156591e-01   \n",
       "75%    7.169673e-01  5.447366e-01  6.758085e-01  8.054898e-01  8.303819e-01   \n",
       "max    5.207001e+00  1.524530e+01  1.510743e+01  4.614776e+00  2.207265e+00   \n",
       "\n",
       "             gray_5        gray_6        gray_7        gray_8        gray_9  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean  -1.244063e-15 -1.336354e-15  3.890250e-16 -1.633194e-16  1.383139e-15   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -5.223107e+00 -5.078521e+00 -5.280877e+00 -4.983875e+00 -5.257274e+00   \n",
       "25%   -6.974575e-01 -6.954582e-01 -6.849231e-01 -6.887822e-01 -6.886303e-01   \n",
       "50%    3.153649e-01  2.950886e-01  2.959727e-01  2.786769e-01  2.704851e-01   \n",
       "75%    8.452803e-01  8.477542e-01  8.385507e-01  8.421420e-01  8.313963e-01   \n",
       "max    1.776906e+00  1.927578e+00  3.170572e+00  3.087497e+00  2.252942e+00   \n",
       "\n",
       "          ...            gray_12       gray_13       gray_14       gray_15  \\\n",
       "count     ...       5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean      ...       9.279387e-16  7.976535e-16 -1.843974e-15  1.496252e-16   \n",
       "std       ...       1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min       ...      -9.337698e+00 -9.710113e+00 -8.481079e+00 -2.234938e-01   \n",
       "25%       ...      -6.647812e-01 -6.901019e-01 -7.313986e-01 -1.952433e-01   \n",
       "50%       ...       1.815574e-01  1.419679e-01  1.501788e-01 -1.387422e-01   \n",
       "75%       ...       7.649559e-01  7.272215e-01  6.978698e-01  1.663564e-02   \n",
       "max       ...       7.547991e+00  4.676281e+00  1.345292e+01  4.154491e+01   \n",
       "\n",
       "         total_gray  lung_density    r_lungsize    l_lungsize      fraction  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.213000e+03   \n",
       "mean   1.259111e-15 -5.339916e-16  3.389416e-16 -1.474196e-16  5.461667e-16   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -5.196343e+00 -5.042037e+00 -4.804644e+00 -2.653969e+00 -2.504743e+00   \n",
       "25%   -7.167310e-01 -7.394767e-01 -6.012113e-01 -5.832742e-01 -4.951508e-01   \n",
       "50%    3.391326e-01 -1.570540e-01 -4.049319e-02  6.333544e-02  7.508578e-02   \n",
       "75%    8.882908e-01  6.750585e-01  5.497750e-01  6.370127e-01  4.880157e-01   \n",
       "max    1.239456e+00  3.945690e+00  7.218072e+00  4.254940e+00  9.529214e+00   \n",
       "\n",
       "             label  \n",
       "count  5216.000000  \n",
       "mean      0.742906  \n",
       "std       0.437073  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       1.000000  \n",
       "75%       1.000000  \n",
       "max       1.000000  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_centered_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Concatenating the Pneumonia and Normal DataFrame into the whole train dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.concat([pne_train, nor_train], ignore_index=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the Summary for this train data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gray_0</th>\n",
       "      <th>gray_1</th>\n",
       "      <th>gray_2</th>\n",
       "      <th>gray_3</th>\n",
       "      <th>gray_4</th>\n",
       "      <th>gray_5</th>\n",
       "      <th>gray_6</th>\n",
       "      <th>gray_7</th>\n",
       "      <th>gray_8</th>\n",
       "      <th>gray_9</th>\n",
       "      <th>...</th>\n",
       "      <th>gray_11</th>\n",
       "      <th>gray_12</th>\n",
       "      <th>gray_13</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>gray_15</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>r_lungsize</th>\n",
       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.875000e+03</td>\n",
       "      <td>3.872000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.429432e-17</td>\n",
       "      <td>1.035587e-15</td>\n",
       "      <td>-2.859361e-16</td>\n",
       "      <td>1.432288e-15</td>\n",
       "      <td>-1.687911e-15</td>\n",
       "      <td>-1.572305e-15</td>\n",
       "      <td>2.312129e-17</td>\n",
       "      <td>5.983457e-16</td>\n",
       "      <td>-5.347407e-16</td>\n",
       "      <td>1.795725e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.003463e-15</td>\n",
       "      <td>-1.405041e-16</td>\n",
       "      <td>1.325993e-15</td>\n",
       "      <td>-1.153257e-15</td>\n",
       "      <td>2.214716e-17</td>\n",
       "      <td>-1.324245e-16</td>\n",
       "      <td>-4.961766e-16</td>\n",
       "      <td>-1.776249e-16</td>\n",
       "      <td>-3.036997e-17</td>\n",
       "      <td>1.758235e-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "      <td>1.000129e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.622537e+00</td>\n",
       "      <td>-1.193113e+01</td>\n",
       "      <td>-6.591133e+00</td>\n",
       "      <td>-6.836367e+00</td>\n",
       "      <td>-5.462090e+00</td>\n",
       "      <td>-5.532481e+00</td>\n",
       "      <td>-5.416726e+00</td>\n",
       "      <td>-5.605821e+00</td>\n",
       "      <td>-5.263822e+00</td>\n",
       "      <td>-5.466022e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.140741e+00</td>\n",
       "      <td>-9.513048e+00</td>\n",
       "      <td>-9.765328e+00</td>\n",
       "      <td>-4.294072e+00</td>\n",
       "      <td>-3.202959e-01</td>\n",
       "      <td>-5.556489e+00</td>\n",
       "      <td>-5.326034e+00</td>\n",
       "      <td>-4.593185e+00</td>\n",
       "      <td>-2.413062e+00</td>\n",
       "      <td>-2.212620e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-7.113177e-01</td>\n",
       "      <td>-5.183361e-01</td>\n",
       "      <td>-5.045907e-01</td>\n",
       "      <td>-5.906616e-01</td>\n",
       "      <td>-5.936750e-01</td>\n",
       "      <td>-6.036763e-01</td>\n",
       "      <td>-5.627076e-01</td>\n",
       "      <td>-5.764903e-01</td>\n",
       "      <td>-5.843064e-01</td>\n",
       "      <td>-5.969427e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.379688e-01</td>\n",
       "      <td>-5.713521e-01</td>\n",
       "      <td>-6.139873e-01</td>\n",
       "      <td>-6.356786e-01</td>\n",
       "      <td>-2.835169e-01</td>\n",
       "      <td>-5.925945e-01</td>\n",
       "      <td>-7.410559e-01</td>\n",
       "      <td>-5.829426e-01</td>\n",
       "      <td>-6.443800e-01</td>\n",
       "      <td>-5.629413e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-5.817248e-01</td>\n",
       "      <td>1.747487e-01</td>\n",
       "      <td>3.064611e-01</td>\n",
       "      <td>4.182271e-01</td>\n",
       "      <td>4.453559e-01</td>\n",
       "      <td>4.518731e-01</td>\n",
       "      <td>4.490913e-01</td>\n",
       "      <td>4.311169e-01</td>\n",
       "      <td>4.207627e-01</td>\n",
       "      <td>4.018429e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>3.403035e-01</td>\n",
       "      <td>2.784785e-01</td>\n",
       "      <td>2.347257e-01</td>\n",
       "      <td>1.963409e-01</td>\n",
       "      <td>-2.099587e-01</td>\n",
       "      <td>5.915080e-01</td>\n",
       "      <td>-1.044068e-01</td>\n",
       "      <td>-1.980214e-02</td>\n",
       "      <td>5.353251e-02</td>\n",
       "      <td>2.417156e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.976019e-01</td>\n",
       "      <td>4.430396e-01</td>\n",
       "      <td>5.512380e-01</td>\n",
       "      <td>6.918241e-01</td>\n",
       "      <td>7.111038e-01</td>\n",
       "      <td>7.223031e-01</td>\n",
       "      <td>7.194858e-01</td>\n",
       "      <td>7.140303e-01</td>\n",
       "      <td>7.276871e-01</td>\n",
       "      <td>7.204210e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>7.167060e-01</td>\n",
       "      <td>6.828665e-01</td>\n",
       "      <td>6.590822e-01</td>\n",
       "      <td>6.139088e-01</td>\n",
       "      <td>-2.606331e-02</td>\n",
       "      <td>7.119083e-01</td>\n",
       "      <td>6.839219e-01</td>\n",
       "      <td>5.571747e-01</td>\n",
       "      <td>6.519757e-01</td>\n",
       "      <td>4.924210e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.555469e+00</td>\n",
       "      <td>1.449552e+01</td>\n",
       "      <td>1.465331e+01</td>\n",
       "      <td>4.466607e+00</td>\n",
       "      <td>2.048557e+00</td>\n",
       "      <td>1.612105e+00</td>\n",
       "      <td>1.770536e+00</td>\n",
       "      <td>3.038273e+00</td>\n",
       "      <td>2.941001e+00</td>\n",
       "      <td>2.085141e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>3.178465e+00</td>\n",
       "      <td>7.360400e+00</td>\n",
       "      <td>4.430320e+00</td>\n",
       "      <td>1.403217e+01</td>\n",
       "      <td>4.002635e+01</td>\n",
       "      <td>1.059814e+00</td>\n",
       "      <td>3.732918e+00</td>\n",
       "      <td>6.759560e+00</td>\n",
       "      <td>4.051833e+00</td>\n",
       "      <td>8.809252e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0        gray_1        gray_2        gray_3        gray_4  \\\n",
       "count  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03   \n",
       "mean   4.429432e-17  1.035587e-15 -2.859361e-16  1.432288e-15 -1.687911e-15   \n",
       "std    1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00   \n",
       "min   -1.622537e+00 -1.193113e+01 -6.591133e+00 -6.836367e+00 -5.462090e+00   \n",
       "25%   -7.113177e-01 -5.183361e-01 -5.045907e-01 -5.906616e-01 -5.936750e-01   \n",
       "50%   -5.817248e-01  1.747487e-01  3.064611e-01  4.182271e-01  4.453559e-01   \n",
       "75%    5.976019e-01  4.430396e-01  5.512380e-01  6.918241e-01  7.111038e-01   \n",
       "max    5.555469e+00  1.449552e+01  1.465331e+01  4.466607e+00  2.048557e+00   \n",
       "\n",
       "             gray_5        gray_6        gray_7        gray_8        gray_9  \\\n",
       "count  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03   \n",
       "mean  -1.572305e-15  2.312129e-17  5.983457e-16 -5.347407e-16  1.795725e-15   \n",
       "std    1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00   \n",
       "min   -5.532481e+00 -5.416726e+00 -5.605821e+00 -5.263822e+00 -5.466022e+00   \n",
       "25%   -6.036763e-01 -5.627076e-01 -5.764903e-01 -5.843064e-01 -5.969427e-01   \n",
       "50%    4.518731e-01  4.490913e-01  4.311169e-01  4.207627e-01  4.018429e-01   \n",
       "75%    7.223031e-01  7.194858e-01  7.140303e-01  7.276871e-01  7.204210e-01   \n",
       "max    1.612105e+00  1.770536e+00  3.038273e+00  2.941001e+00  2.085141e+00   \n",
       "\n",
       "           ...            gray_11       gray_12       gray_13       gray_14  \\\n",
       "count      ...       3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03   \n",
       "mean       ...      -1.003463e-15 -1.405041e-16  1.325993e-15 -1.153257e-15   \n",
       "std        ...       1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00   \n",
       "min        ...      -6.140741e+00 -9.513048e+00 -9.765328e+00 -4.294072e+00   \n",
       "25%        ...      -5.379688e-01 -5.713521e-01 -6.139873e-01 -6.356786e-01   \n",
       "50%        ...       3.403035e-01  2.784785e-01  2.347257e-01  1.963409e-01   \n",
       "75%        ...       7.167060e-01  6.828665e-01  6.590822e-01  6.139088e-01   \n",
       "max        ...       3.178465e+00  7.360400e+00  4.430320e+00  1.403217e+01   \n",
       "\n",
       "            gray_15    total_gray  lung_density    r_lungsize    l_lungsize  \\\n",
       "count  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03  3.875000e+03   \n",
       "mean   2.214716e-17 -1.324245e-16 -4.961766e-16 -1.776249e-16 -3.036997e-17   \n",
       "std    1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00  1.000129e+00   \n",
       "min   -3.202959e-01 -5.556489e+00 -5.326034e+00 -4.593185e+00 -2.413062e+00   \n",
       "25%   -2.835169e-01 -5.925945e-01 -7.410559e-01 -5.829426e-01 -6.443800e-01   \n",
       "50%   -2.099587e-01  5.915080e-01 -1.044068e-01 -1.980214e-02  5.353251e-02   \n",
       "75%   -2.606331e-02  7.119083e-01  6.839219e-01  5.571747e-01  6.519757e-01   \n",
       "max    4.002635e+01  1.059814e+00  3.732918e+00  6.759560e+00  4.051833e+00   \n",
       "\n",
       "           fraction  \n",
       "count  3.872000e+03  \n",
       "mean   1.758235e-16  \n",
       "std    1.000129e+00  \n",
       "min   -2.212620e+00  \n",
       "25%   -5.629413e-01  \n",
       "50%    2.417156e-02  \n",
       "75%    4.924210e-01  \n",
       "max    8.809252e+00  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pne_centered_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gray_0</th>\n",
       "      <th>gray_1</th>\n",
       "      <th>gray_2</th>\n",
       "      <th>gray_3</th>\n",
       "      <th>gray_4</th>\n",
       "      <th>gray_5</th>\n",
       "      <th>gray_6</th>\n",
       "      <th>gray_7</th>\n",
       "      <th>gray_8</th>\n",
       "      <th>gray_9</th>\n",
       "      <th>...</th>\n",
       "      <th>gray_12</th>\n",
       "      <th>gray_13</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>gray_15</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>r_lungsize</th>\n",
       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.213000e+03</td>\n",
       "      <td>5216.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.179186e-17</td>\n",
       "      <td>6.584712e-16</td>\n",
       "      <td>-4.180364e-16</td>\n",
       "      <td>8.575707e-16</td>\n",
       "      <td>-1.411405e-15</td>\n",
       "      <td>-1.029298e-15</td>\n",
       "      <td>-1.494204e-17</td>\n",
       "      <td>1.785807e-16</td>\n",
       "      <td>-5.808663e-16</td>\n",
       "      <td>1.399188e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.558844e-16</td>\n",
       "      <td>8.210883e-16</td>\n",
       "      <td>-1.295019e-15</td>\n",
       "      <td>2.215763e-17</td>\n",
       "      <td>-1.511657e-16</td>\n",
       "      <td>-3.958149e-16</td>\n",
       "      <td>-1.839020e-17</td>\n",
       "      <td>-4.491125e-17</td>\n",
       "      <td>1.502517e-16</td>\n",
       "      <td>0.742906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>0.437073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-2.057588e+00</td>\n",
       "      <td>-1.193113e+01</td>\n",
       "      <td>-6.591133e+00</td>\n",
       "      <td>-6.836367e+00</td>\n",
       "      <td>-5.462090e+00</td>\n",
       "      <td>-5.532481e+00</td>\n",
       "      <td>-5.416726e+00</td>\n",
       "      <td>-5.605821e+00</td>\n",
       "      <td>-5.263822e+00</td>\n",
       "      <td>-5.466022e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.513048e+00</td>\n",
       "      <td>-9.765328e+00</td>\n",
       "      <td>-1.039268e+01</td>\n",
       "      <td>-3.202959e-01</td>\n",
       "      <td>-5.556489e+00</td>\n",
       "      <td>-5.326034e+00</td>\n",
       "      <td>-4.593185e+00</td>\n",
       "      <td>-3.959139e+00</td>\n",
       "      <td>-4.624665e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-7.113177e-01</td>\n",
       "      <td>-5.466557e-01</td>\n",
       "      <td>-5.513100e-01</td>\n",
       "      <td>-6.071264e-01</td>\n",
       "      <td>-6.011244e-01</td>\n",
       "      <td>-6.178521e-01</td>\n",
       "      <td>-5.888748e-01</td>\n",
       "      <td>-5.960766e-01</td>\n",
       "      <td>-5.975932e-01</td>\n",
       "      <td>-6.098580e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.976870e-01</td>\n",
       "      <td>-6.213674e-01</td>\n",
       "      <td>-5.861699e-01</td>\n",
       "      <td>-2.467378e-01</td>\n",
       "      <td>-6.183466e-01</td>\n",
       "      <td>-7.469410e-01</td>\n",
       "      <td>-5.930893e-01</td>\n",
       "      <td>-6.336148e-01</td>\n",
       "      <td>-5.282762e-01</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-4.229577e-01</td>\n",
       "      <td>1.270526e-01</td>\n",
       "      <td>2.443536e-01</td>\n",
       "      <td>3.327281e-01</td>\n",
       "      <td>3.495124e-01</td>\n",
       "      <td>3.515523e-01</td>\n",
       "      <td>3.400612e-01</td>\n",
       "      <td>3.310090e-01</td>\n",
       "      <td>3.343052e-01</td>\n",
       "      <td>3.196076e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.154577e-01</td>\n",
       "      <td>1.830649e-01</td>\n",
       "      <td>1.550669e-01</td>\n",
       "      <td>-1.727036e-01</td>\n",
       "      <td>4.331716e-01</td>\n",
       "      <td>-1.205727e-01</td>\n",
       "      <td>-3.571398e-02</td>\n",
       "      <td>3.359796e-02</td>\n",
       "      <td>2.056964e-02</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.135662e-01</td>\n",
       "      <td>4.549637e-01</td>\n",
       "      <td>5.621982e-01</td>\n",
       "      <td>6.960990e-01</td>\n",
       "      <td>7.111038e-01</td>\n",
       "      <td>7.223031e-01</td>\n",
       "      <td>7.152444e-01</td>\n",
       "      <td>7.183828e-01</td>\n",
       "      <td>7.276871e-01</td>\n",
       "      <td>7.247261e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>6.890247e-01</td>\n",
       "      <td>6.664623e-01</td>\n",
       "      <td>6.139088e-01</td>\n",
       "      <td>-6.284239e-02</td>\n",
       "      <td>7.120222e-01</td>\n",
       "      <td>6.633231e-01</td>\n",
       "      <td>5.580737e-01</td>\n",
       "      <td>6.446336e-01</td>\n",
       "      <td>4.960230e-01</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.555469e+00</td>\n",
       "      <td>1.449552e+01</td>\n",
       "      <td>1.465331e+01</td>\n",
       "      <td>4.466607e+00</td>\n",
       "      <td>2.118944e+00</td>\n",
       "      <td>2.270051e+00</td>\n",
       "      <td>2.475254e+00</td>\n",
       "      <td>3.038273e+00</td>\n",
       "      <td>2.941001e+00</td>\n",
       "      <td>2.572576e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.360400e+00</td>\n",
       "      <td>4.430320e+00</td>\n",
       "      <td>1.403217e+01</td>\n",
       "      <td>4.002635e+01</td>\n",
       "      <td>1.905467e+00</td>\n",
       "      <td>3.732918e+00</td>\n",
       "      <td>8.989145e+00</td>\n",
       "      <td>4.051833e+00</td>\n",
       "      <td>8.809252e+00</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0        gray_1        gray_2        gray_3        gray_4  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean   1.179186e-17  6.584712e-16 -4.180364e-16  8.575707e-16 -1.411405e-15   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -2.057588e+00 -1.193113e+01 -6.591133e+00 -6.836367e+00 -5.462090e+00   \n",
       "25%   -7.113177e-01 -5.466557e-01 -5.513100e-01 -6.071264e-01 -6.011244e-01   \n",
       "50%   -4.229577e-01  1.270526e-01  2.443536e-01  3.327281e-01  3.495124e-01   \n",
       "75%    6.135662e-01  4.549637e-01  5.621982e-01  6.960990e-01  7.111038e-01   \n",
       "max    5.555469e+00  1.449552e+01  1.465331e+01  4.466607e+00  2.118944e+00   \n",
       "\n",
       "             gray_5        gray_6        gray_7        gray_8        gray_9  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean  -1.029298e-15 -1.494204e-17  1.785807e-16 -5.808663e-16  1.399188e-15   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -5.532481e+00 -5.416726e+00 -5.605821e+00 -5.263822e+00 -5.466022e+00   \n",
       "25%   -6.178521e-01 -5.888748e-01 -5.960766e-01 -5.975932e-01 -6.098580e-01   \n",
       "50%    3.515523e-01  3.400612e-01  3.310090e-01  3.343052e-01  3.196076e-01   \n",
       "75%    7.223031e-01  7.152444e-01  7.183828e-01  7.276871e-01  7.247261e-01   \n",
       "max    2.270051e+00  2.475254e+00  3.038273e+00  2.941001e+00  2.572576e+00   \n",
       "\n",
       "          ...            gray_12       gray_13       gray_14       gray_15  \\\n",
       "count     ...       5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean      ...      -3.558844e-16  8.210883e-16 -1.295019e-15  2.215763e-17   \n",
       "std       ...       1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min       ...      -9.513048e+00 -9.765328e+00 -1.039268e+01 -3.202959e-01   \n",
       "25%       ...      -5.976870e-01 -6.213674e-01 -5.861699e-01 -2.467378e-01   \n",
       "50%       ...       2.154577e-01  1.830649e-01  1.550669e-01 -1.727036e-01   \n",
       "75%       ...       6.890247e-01  6.664623e-01  6.139088e-01 -6.284239e-02   \n",
       "max       ...       7.360400e+00  4.430320e+00  1.403217e+01  4.002635e+01   \n",
       "\n",
       "         total_gray  lung_density    r_lungsize    l_lungsize      fraction  \\\n",
       "count  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03  5.213000e+03   \n",
       "mean  -1.511657e-16 -3.958149e-16 -1.839020e-17 -4.491125e-17  1.502517e-16   \n",
       "std    1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min   -5.556489e+00 -5.326034e+00 -4.593185e+00 -3.959139e+00 -4.624665e+00   \n",
       "25%   -6.183466e-01 -7.469410e-01 -5.930893e-01 -6.336148e-01 -5.282762e-01   \n",
       "50%    4.331716e-01 -1.205727e-01 -3.571398e-02  3.359796e-02  2.056964e-02   \n",
       "75%    7.120222e-01  6.633231e-01  5.580737e-01  6.446336e-01  4.960230e-01   \n",
       "max    1.905467e+00  3.732918e+00  8.989145e+00  4.051833e+00  8.809252e+00   \n",
       "\n",
       "             label  \n",
       "count  5216.000000  \n",
       "mean      0.742906  \n",
       "std       0.437073  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       1.000000  \n",
       "75%       1.000000  \n",
       "max       1.000000  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/matplotlib/font_manager.py:1241: UserWarning: findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans.\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrmat = train_centered_df.corr()\n",
    "f, ax = plt.subplots(figsize=(12, 12))\n",
    "sns.heatmap(corrmat, vmax=1, square=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the Correlation coefficient matrix, We see that for lable, the most positive correlated features are lung_density, gray_14, the most negitive correlated features are gray_0, gray_15, l_lungsize and fraction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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so30AY2PjHJ18cnJytptAvTJgwABSUlIYNmwYaWlptGnThqZNm1KkSBF1h591W6mpqahUqly3lZXo+AVBEPKSjxH/f6d08mJtbc3Tp0+Jj4+nePHiQMa9vrNO2bwSGxuLm5ub+hODXC7HxcUFNzc3ihQpQunSpblz5w7W1tYA3Lp1C6lUiqWl5Wv3QZzVIwiCkJf3cFaPpaUl9erVw9fXl6SkJG7dukVAQECunxb279/PsGHDePr0KTKZjP/973/o6+vzzTffANClSxf8/PyIjY3l2bNnLFq0iDZt2mBoaPjafRAjfkEQhLzI5e9ls8uWLWPmzJl88803SKVSevXqRbdu3YiJicHV1ZW1a9dSv359+vfvz8OHD2nTpg1yuRx7e3s2bNiAvr4+AN999x1paWl07dqV1NRUHB0dmTFjxhvzxemcBUSczvnhidM5C5+3Pp1zu7fGdY16vLnD/ViIEb8gCEJexLV6BEEQChnR8QuCIBQyn+lF2kTHLwiCkBeFoqD34L0QHb8GZs2ahUwmY/78+bmWT5gwgdjYWDZt2vTWWRKJhNFzR1KlhhXpaeksmLCImHsxOerMC5hN6MEw9m7OuLDTjnNbeXD3AQBX/7zGT/PXab0PkVevs8hvHRtWZL/YU8ipcPzW/4Keri6d27Wka4c2pKSmMsl7AfFPn2FibMScqeMoXqxovjMlEgnfzxuLdY0qpKelM3u8L9H3HuSos2STD38cPMWuTYEYGhkye9V0zIuakZKUwvQRs3kW/1yrNitVKuYe+JMbsc+R6ukwo319KhU3U5dvPH2d4Kv3kUjg26bVca5WgcSUNCb9Fk5yuhyprg5zOjekpKk2B1IlSFv2Qad0RVDISQtaj+rZY3WpXoPW6FVviEqlQh62D8XN8yDVR7+9FxJDE0hPJXXfWkhO1K7dIVHciEtEX1eH6c7VqVTUWF0ecP5vgm8+QiKBgXaWOFcpjUqlotWGUCoVyWhrbYsijGyc8xz0jzlb8538PEf84jz+13j27BkTJkxg8+bNedb59ddfc72qnraatm6CvoE+wzuOwn/ezwybNiRHnYET+2NeNLNTKmdZjpuXbzKm23jGdBv/Vp3+ui07mTF/KWmpadmWp8vl+Czzx3/xHDas9GXnniDinsSz/ff9WFexJMBvIe3buLBm4zatcpu1/hoDA30GdhjGirlrGD3juxx1hn7/LeZFM78g09mjPdcjoxjceQSH9hxl4GhPrbIBjl9/QKpcScBAF0a51GbRoUvqsoSUNLaevUXAAGdWezix4OBFAAIv3aNq6SKs6+dMy5oV2Xg657VWNKH7pS0SPSmpm+eQ/sdOpM49MwsNjNCza07Kptmkbl+I1MUdAL06Tihj75H6yzzkf51B2ri9du2+8y9pCiUB3ewZ2bgqi0JvqssSU9PZGnmfjV3r49ehHgtOZZTdf55M9VJm/NTFjp+62Gnd8RZktsbe02WZC9pHOeKPjIxk1qxZ3L59G2tra+zs7Lh8+TINGjTgwoULPHv2jAcPHrB27VpMTEzw9fUlKiqK+Ph4KleuzMSJE/n666+ZPn06sbGx+Pv7q7c9fvx4ihcvzuTJk1+7DykpKbRu3Zq2bdvSqlWrXOvcunWLVatW0aNHD27fvv1O2v6VfU3OhkQA8Nf5v/iyzpfZyh1dv0apVHLmeIR6mc1X1pS0KMmiHQtITUlj1Y9+3L+j3emDFcuVZcncqfwwc0G25Xfu3adShXIUMc94w7GtXZM/L13l/KWrDPDoCsDXDvasWb81xzY1UafBV5wOOQPAlfPXqF7bJlu5s6sTSqWK08fPqJdt/WknOjoZYxeL8mV48m+8VtkAF/6Jo0kVCwBqVyjB1YdP1WVGUj3KFjEmOU1BcrociUQCgHXpItyLyxhly1Ll6OloN47SqWCN4u5lAJQxd9CxsMwsTE9D9fwJSA2Q6BvAy7Ov5ecOw8v9kJiXQCXT7pPOhZhnNK6U8e3R2hZFuPY481ODoZ4uZc0MSU5XkCxXqEeJf/2byGNZKoN+/xMDPV3GN7XGsljeV4L8GLM19pnO8X90I/6EhAQGDx5MixYtOHPmDN9//z07d+5Ul4eHhzN58mSOHj1KrVq1GDlyJNWqVePw4cOcO3eORo0aMW3aNCDjW22hoaHqa1fLZDKOHDmS6zfk/ksqlbJ3716mT5+OsbFxjvKUlBTGjBnD9OnTKV269DtqPRibmSBLlKmfKxVKdHQzXiZLG0tcOjmzfuHGbOs8eRzPLyu2Mbb7BLYs/4XJyyZpnd/im6bo6eUcD8hkMkyzXObVxNiIxBcyZElJmJqaqJe9kMlyrKsJEzMTZAlZ2q1UoqurC0AVmy9o3bkFaxb8nGM9pVLJqh1L6D7AjdPHwrXKBpClpWNqIFU/15VIkGcZxZUpYkwXv2B6+h/GvUHGKLOIkQFhd2LpsiqYjaej6FTvC62yJfpGqFKzXFRLpQRJ5r+mKjEeo2/nYOj5I/I/j2Spp8Kg50Skds1R3InUKluWrsDUIPP11pWQvd2mhrj9Eo779rO416kIQEljfQbYVWZtZzsG2lky5fDVTy5bUyqlSuPHp+SjG/EfP34cAwMDBg0ahEQiwdbWlu7duxMZmfGHXbFiRerXr6+uv3r1asqUKYNEIiEmJgZzc3NiY2MBqFu3LpUrV2b//v306dOHgwcPUrlyZapXr/7G/dDV1aVUqVJ5ls+cOZPGjRvTrFkzrl279patzpSUKMPYJHOeWEdHglKR8c/QqmtzSlmUYNGOBVhUKEN6upzY6Fgiwy+jeHkQ6krEVUpalMx122/DxMSEpKQk9XNZUjLmZiaYGBuTlJSsXmb2hotD5UWWKMPYNPMNViKRqNvUtlsrSlmUxG/nEspWtCA9Tc7D+7GEhZwFYFj30VSuWoklAT50buyuXfv0pcjSMr+lqVSp1CP40FsPiUtMZv9I14y8zSeoW7Ek60Ov069xNbraVeHGo2eM33manV65fzp8HVVaMhL9LF+xl0jUI01dq6+QmBQhefUEAAy6j0P54CbKh3cBSN3mi6S4BQZdx5Di/33+2y3VJSkt8wCmUkVmu/95QlxSKvv6Ns5od+BF6pYtQo3S5ujpZHzaqFeuKI9fZFwY7NUnoU8hW2Of2BSOpj66jv/Ro0dYWFhkeyErVKig7vj/2xlfv36d4cOH8/jxYywtLSlRogRZv4zcqVMnAgMD6dOnD7t379ZotP8mgYGBXL9+nW3btJvPfp0r567SqHkjQvadoLptde5cv6suWzPnJ/XPnmP7EP/4KREh5xg8+VsSniawzW8HVapb8TjmcW6bfitWlhX5OzqG5wmJGBsZ8uelK/Tr5UZM7GNOhEXwVQ0bToZHYFsn72uAv86liCs4tmjMkb3HqWVbg9vX76jLls9erf550Lj+PHn8hLCQs/Qb7sGjh/8S9NshUpJSUCi0/yetW6kkf9yIoVXNikRGP8G6dBF1mbmhPgZSXfR1dZBIJJgZSklMScfcUF/9KaG4iQEvUtO1ylZG30S3al0U1yPQKWeF6t/MaTpVigzk6aDIeFNSpSaDgTF6Dq6oEuNRXA2D9DStpyTqli3KiXtxtLQuQ2Tsc6qWyHzjNjfQw0AvS7sN9EhMleMfcZcihlL62VYmKi6RsmaGWnW8BZmtMXFWz4dRtmxZYmJisr2LP3z4UF2e9UV+/Pgxo0aNYsWKFTg7OwNw8OBBDh8+rK7TqVMnlixZwsWLF7lw4QJLlmh+R5287Nmzh7t379K4ccZoJC0tDblcTv369Tl37txbbftkUCh2X9uxfPcSJBIJPmMX0m2QGw/uxXD6cFiu6/yychtTlk3CwaUhCrmC+WMW5FpPG/sPHScpOZluHdsyccQgBo+ZgkqlorNrS8qUKkmPzq5Mmf0/+gwdh1RPiu+PE7XKCQk6QUPH+vwcmPEV+5lj59NrcHei7z3gxKHQXNcJ3HaAH5dOpqO7Kzq6OswcO0/rdjpXK0/4nVj6rjsKKvDuaM+msCgqFjelmU15wu8+os/PR9GRSKhbqSSNrMpQtXQRvPdGsOPcLeQKFdPb1X9zUC4UN86jY1kTg95TAEg78DN69i1RPX2M4tZFlLF3MegzFVQqlNE3Ud67ivLxfQxcv0WvtiNIdEg7kHMaTKN2VylF+P14PH89h0qlwrt5DTZd+IeKRY1o9kUpztx/St9fzyEhY4TtULE4NUubM+XwVU7ei0NPR4J38xqfXLbGPtMR/0d3rR6ZTEaLFi3w9PRkwIABREVF8e2332JtbU2DBg04e/as+rTJO3fu0KZNGzZu3IiDgwO3bt1i7NixREVFceXKFaTSjNHYoEGDiIuLo2zZsqxalf9rd0yalDFnntfpnKtWrSIsLCxfp3OKa/V8eOJaPYXP216rJ2mpl+ZZo1a/udJH4qM7uGtiYsLKlSsJDg6mQYMGzJ49m6ZNm6o78aysrKyYOHEi48ePx87OjlGjRuHm5oaenh63bt1S1+vSpQvXrl2jS5cuH7IpgiB86lQqzR+fkI9uqufp04zT6H7//Xf1Mh8fH1QqVbbbl70ycOBABg4cmG2Zp2f287krVKhAiRIlcHLSbsSX10j/lWHDhjFs2DCtti0IwkfsM53q+ehG/HK5nD59+hAWljGffevWLfbu3UuzZs3yva0XL14QFRXFsmXL6NatW66fGgRBEPKkVGn++IR8dCP+UqVKsXDhQmbPnk1MTAzFihWjf//+tG+f/28mPnz4kJ49e1K7dm0GDx6sXn7kyBEmTJiQ53rNmzdnwYJ3d4BUEIRPlDir58Np3bo1rVu3fuvtWFtbc+HChRzLmzdvnutyQRCErFSf6VTPR9nxC4IgfBQ+sSkcTYmOXxAEIS+f6bV6RMcvCIKQFzHiFwRBKGTk4uCuIAhC4SKmegRBEAoZMdUjvEv/puf/NnnvSkFeL+d05IYCyy7IdicpUgss20Cn4L64+EKeUmDZADdyftk/X8TpnIIgCIWNGPELgiAUMqLjFwRBKGTEJRsEQRAKl0/tXrqaEh2/IAhCXkTHLwiCUMiIs3oEQRAKGTHiFwRBKGRExy8IglC4qBRiqkcQBKFwESN+QRCEwuVzPZ3zo7vZ+scsLi6OpKSk95ohkUiY7juRzfvXsn7XKipaVsi1jt8vi+net3O25S5tnPDx836r7Enzx/Fz4CpW/7qUCpblc62zdLMvXfp0AMDQyJCF6+fi//tylm1ZQNHiRbTOB4i8ep1+wyfmWB5yKpweA0fiMXgMvwYGAZCSmsroybPpO3Q8Q8dNI/7pM61zC7LtGa/592zZ/xPrd62iUh6v+eo8XnNfv5la5b7a7mSf8WzYuxr/35ZTMY92L9+yELe+HQEwNTNhyUYf1u5azoa9q6ltV1PrbO8FP7D9wDo27V5DpS9yb/dP25bS09MNAANDA5av9+WXvWtZu3UpxUoU1SpbY5/pzdbf2PFHR0djY2NDdHT0h9gfjfXp04fly5e/14zAwEBcXV2BjE6/ZcuWxMfHv9dMlzZO6BsY0Nt1EIvnrGSC98gcdUb+MIQixcyzLZs0ewyjpgxFR0f79/Jmrb/GwECfgR2GsWLuGkbP+C5HnaHff4t50czszh7tuR4ZxeDOIzi05ygDR3tqnb9uy05mzF9KWmpatuXpcjk+y/zxXzyHDSt92bkniLgn8Wz/fT/WVSwJ8FtI+zYurNm4Tevsgmy7SxsnDAz08XD9lsVzVjHBe1SOOiN/8MrlNR/L6CnDkLzFa/5Nm6/RN9CnX3svls9ZzZgZw3PU+W7SoGzt7j2kB2dPnWNQlxHMGD2H7+eN1Sq7RdtmGBjq06PtABbOWs4k7zE56oyZPJQiRTPfUHv168qNa7fo1X4Qu7fvZ9jYgVpla0yZj8cnRIz4X6NDhw7s378fgJSUFGQy2XvPrNewDqHHwwCI/PMqNetUy1beot03KJUqTh0Ny7b8YsRlZn3v+1bZdRp8xemQMwBcOX+N6rVtspU7uzqhVKo4ffyMetnWn3aybukmACzKl+HJv9q/MVYsV5Ylc6fmWH7n3n0qVShHEXMzpFIptrVr8uelq5y/dJWmDe0A+NrBnvCIC1pnF2TbbRvW4dTxcAAi/7yS4zVv2c5AemWkAAAgAElEQVQZlVLJyRyveeRbv+Z1G9RWt+ny+avU+E+2i2uzjHYfC1cv2+y/g9827QFAV1ePtJTsb9SasmtYV92mS39e4au61bOVt2rvglKp4sTR01nWqcOJYxnP/zgaSmPHBlpla0olV2r8+JTkq+O3sbHhzJnMP/xVq1bRp08fAHbt2oW7uzuzZ8+mYcOGNGnShOnTpyOXywGQy+X4+vri4ODA119/zeLFi3F2ds62vdfZuXMnLi4u1KtXj++//57k5GR1mVKpZMOGDbRq1Qp7e3s8PT25efNmtv0OCAigVatW2Nra4uHhoS6Xy+XMnDmTxo0b4+DgQO/evYmMjFS3ydnZGYVCQbt27QBo164d+/fvx97enqCgIHXGixcvqFu3LtevX8/PrzQHUzMTEhMy32CUCiW6uroAVK1mhWuXVqzw8c+xXvCeI/CWnzZNzEyQZc1WZmZXsfmC1p1bsGbBzznWUyqVrNqxhO4D3LJ1EPnV4pum6OnlPOwkk8kwNTHJ3E9jIxJfyJAlJWFqaqJe9uIt3pgLsu0mZiYkJrzI3OZ/XvO2XVqyPI/XXKV6uxfdxNSEF4mZ7Vb8p91turTAz/enbOu8SHhBakoaJUoVZ/aKaSyft0arbFMzExITM9utyNJu62pVaN+lFUvnr86xzouXvyvZiyTMzE21ytbYZzrif6cHd8+fP4+joyOnTp3ixo0b9O7dm8aNG9O6dWv8/f05evQoO3bsoGTJksyaNYsHDx5otN2wsDBmzZqFv78/9evXZ8eOHezevRsnJycAtmzZwsaNG/Hz86NKlSrs2LGDfv36ERwcjJmZGQAHDhxg06ZNGBsbM2rUKBYuXMiaNWvYs2cP4eHhBAUFYWpqyrJly/Dx8WHLli3qfF1dXfbt24eLiwv79u2jQoUKnDlzhsDAQNq0aQNAcHAwlStXplq1ajkbkA8vEmWYmBqrn0t0dFC8vFBUh25tKV22FOt+W0m5imVJT0/nwf2HhB7XvrPNSpYowzhrtkSizm7brRWlLErit3MJZStakJ4m5+H9WMJCzgIwrPtoKletxJIAHzo3dn8n+/OKiYlJtmMrsqRkzM1MMDE2JikpWb3MzFT7TqAg2y57zWvesVtbyrx8zctXLEt6upyY+w/VnxDeluyFDBOTzGydLO1u1601pSxKsebXZZTL0u7Tx89QtZoV81Z7s3jmSs6HXdQq+79/6zo6mdmdurtSpmxpAn5f/bLd6Ty4H/NynZdv9qbGJDx/keu235XP9eDuO+34DQ0N8fLyQiKRULNmTWxsbLh9+zYAv//+O4MHD6ZSpUoATJ06lT179mi03cDAQFq2bImDgwMAvXr1YseOHeryrVu3MmTIEHWn6+HhwdatWwkODqZbt24A9O3bl9KlSwPQqlUr/P0zRlAGBgbExsby+++/4+joyKhRozSaJ3dzc8PDw4OnT59SrFgx9uzZQ+fOnd+43ptcOBtJs5ZNORh4lNp2Nbn512112aJZK9Q/Dxv/LXGPn7yzTh/gUsQVHFs05sje49SyrcHt63fUZctnZ468Bo3rz5PHTwgLOUu/4R48evgvQb8dIiUpBcV7OO/ZyrIif0fH8DwhEWMjQ/68dIV+vdyIiX3MibAIvqphw8nwCGzraHeQEQq27dlf81rc/OuWuux/ubzm76rTh4wpQscWTTi89xhf2dbkVpZ2L53tp/55yLgBxP37hNPHz/DFl5b4rJ3FpCEzuHntVm6b1cifZy/h3OprgvYcoY5dLW5kafeCmcvUP4+YMJh/Hz/h5LEwrG2scGrehMgLV3FyacK5cO2n9zTynkbycXFxTJ06lYiICAwNDXF3d2f48JzHV1xdXYmJicm2LCkpibFjxzJkyBCuX79Op06dMDIyUpfXqFEj28A1N++04y9RogQSiUT9XCqVonx5rYvY2FgsLCzUZSYmJhQrVkyj7T569IiaNbP/U796AwF48OABPj4+LFy4UL1MLpdn+0RRokQJ9c96enrq/WrXrh2pqan8+uuvLFy4kFKlSjF48GDc3V8/cqtTpw6VKlUiKCgIJycnLly4wNKlSzVqz+scPRBCYyd7Nu/zB4mEaaNm03eIO//ciybk4Mm33v7rhASdoKFjfX4OXAXAzLHz6TW4O9H3HnDiUGiu6wRuO8CPSyfT0d0VHV0dZo6d9872Z/+h4yQlJ9OtY1smjhjE4DFTUKlUdHZtSZlSJenR2ZUps/9Hn6HjkOpJ8f0x59lAmirIth85EEIjpwZs3rcWiUTC1FGz8Hz5mh9/z6/58QMncHC0Z32gHxKJhB/HzMVjSA/u343Os90jfhiCgYE+E2ZlHIR+kfCCsf1/yHf24f3HaeLUkG37f0YikfDDSG/6e3nw9937HDt4Itd1ftnwKz4rvNm67yfS0tIZ55XzmNC79L5G/GPGjKFChQqEhoZy//59Bg8ejKWlpXpK+ZVXxxhfWbJkCSEhIfTu3RuAy5cvU6dOHbZv356v/Hx1/DpZPoICPH36VON1y5Url+2dKzk5WeP1y5Qpk+OsotjYWKytrdXlo0ePpm3bturyO3fuqEf4r3Pv3j1q166Nm5sbMpmM4OBgJk+eTP369d+4bufOnQkKCiIpKQlHR0eKFy+uUXteR6VSMXNi9gN2d2/9naPeqoU/5VgWcfo8EafPv1X2/En/y7bs71v/5Ki39n/r1T/Hxz1lpMcErTP/q3zZMvyydgkAri2/US9v1tSBZk0dstU1MjRk0ewp7yS3INue8Zr7ZFv2IV/zud8vzLbsXi7tXvO/deqftenk88qeMSH7m+WdXNq9fEHm8Y2U5FRGDZz0TvI1ko8Rf0JCAgkJCTmWm5ubY26eeVbU33//zdmzZ1m8eDGGhoZYW1vj6enJli1bcnT8WYWHh7Nx40Z2796NyctjXleuXKFWrVqa7+RL+Tq4+8UXX7B3715SUlKIiorKdnDzTbp27cq6dev4559/SElJwcfHJ9ubyJvWPXLkCH/88QdyuZzff/+dS5cuqcvd3Nzw8/Pj3r17qFQqjhw5QocOHfjrr7/euO2QkBCGDx9OdHQ0JiYmlChRAj09PfWxgVf09fWBjIO4r3Ts2JGLFy+yZ88eunTpolFbBEH4dKjkmj82btyIi4tLjsfGjRuzbfPmzZsULVqUkiVLqpdZWVkRFRWV534oFApmzJjBd999R+XKldXLr1y5QlRUFK1ataJx48aMGjWK2NjYN7YrXyP+6dOnM3/+fBo1akT16tXp1q0b586d02jd/v378/jxY7p27Yq+vj7du3dHT08PqfTNN4K2s7PDx8eHuXPn8ujRIxwcHGjSpIm6fODAjHN5Bw0aRFxcHOXLl8fHxwd7e/s3brt37948fPiQnj178uLFCypUqMCSJUuyTUsBlCpVCmdnZ3r06MH06dNxc3OjdOnSNGrUiMjISPWBZkEQPh+qfIz4PT09cz3Ol3W0DxlnqWWdkwcwMjIiJSXvG9Pv3buX5ORk9VmUr5QoUYI6derQp08fFAoFs2fPZvDgwfz+++/qM6RyI1G97flgGrp06RIVKlRQz7XLZDJsbW05ePAglpaWH2IX3ouZM2eip6fH5MmT87VerTIOb670nhjp6hdY9unIDQWW3bh2vwLLTlKkFli2gc6bB1fvywt53p3Zh3DjX80GpnmJa6X5gK7kwT80qnf48GGmTZtGeHjmQfoTJ04wfvx4zp49m+s6vXr1onHjxrkeAM4qPj6eRo0asXfvXr788ss8632wL3Dt3buXH374AZlMRlpaGitXrsTS0vKT7fQfPnxIWFgY+/fvp2fPngW9O4IgvAcqpeYPTVlbW/P06dNsVwG4ffs2VatWzbV+XFwc58+fp2PHjtmWP3nyBB8fH549y7xUSVpaxpfpDA0NX7sPH+wibSNHjsTb2xtnZ2fkcjn16tVjzZo1PH36FGdn5zzXK1asGMeOHftQu6mxbdu2ERAQwMiRI7Gysiro3REE4T3IT4euKUtLS+rVq4evry/Tp08nJiaGgIAAhg0blmv9ixcvUrp0aSpWrJhteZEiRTh48CAymYzJkyeTnJyMt7c3jRo1ynbWY24+2FSPkJ2Y6vnwxFTPh/epT/U8atZM47plQkI0rvv48WNmzpxJREQEUqmUXr16MWzYMGJiYnB1dWXt2rXqMws3bNjA/v372blzZ47t3L59m3nz5hEZGYlKpaJZs2ZMmTKFokVff/E60fEXENHxf3ii4//wPvWOP9axmcZ1LU6EvFXWhySuxy8IgpAHlVLy5kqfINHxC4Ig5OF9zPF/DETHLwiCkAeVSoz4BUEQChUx4hfeqXuJjwos+9+1vQssuyAPsBbkgWWVTPvbQr59eAH2XroFd2D5XVAqxIhfEAShUBEHdwVBEAoZ0fELgiAUMp/rt5xExy8IgpAHMeIXBEEoZMTpnIIgCIWMQpzVIwiCULiIEb8gCEIhI+b4BUEQChlxVo8gCEIhI0b8giAIhYxC+cHuTvtBfZCOPy0tjadPn1KmTJk31r1//36OW4wVJhKJhCVLZ1Hrq+qkpabx3bBJ3Lnzt7p88JA+ePR2Q6WC+fOWERyUcVvKG7fCuH3rHgBnzpznxxkL8p2tVKmYe+BPbsQ+R6qnw4z29alU3ExdvvH0dYKv3kcigW+bVse5WgUSU9KY9Fs4yelypLo6zOnckJKmRlq1+/t5Y7GuUYX0tHRmj/cl+t6DnL+bTT78cfAUuzYFYmhkyOxV0zEvakZKUgrTR8zmWfzzfGe/Enn1Oov81rFhhW+25SGnwvFb/wt6urp0bteSrh3akJKayiTvBcQ/fYaJsRFzpo6jeLHX3/UoL0qlktnL1xF15x/0pXp4jxlMpfIW6vKftwcSdPw0JsZGDOjeHicHWx4+juMHn5WoVFDEzBSfH4ZjZGigZfZ6ou7+g75Uivfob/+TvZegkJfZ3dplZvv6oVKpMrInfad99rKfiLr9d0b2OK/s2dt2E3Q8FBNjYwb06ICTgx0PH8Xxg8/yl+02wWfyKK2yNfW5TvV8kLczDw8PQkND31gvJCSE/v37a7xdGxsbzpw58za79tFp36ElBgYGuHzjxvRpPsydP0VdVqJEMQYN6o3LN11p19aDJUtnAWBlVZmLF6/SprU7bVq7a9XpAxy//oBUuZKAgS6McqnNokOX1GUJKWlsPXuLgAHOrPZwYsHBiwAEXrpH1dJFWNfPmZY1K7LxdJRW2c1af42BgT4DOwxjxdw1jJ7xXY46Q7//FvOi5urnnT3acz0yisGdR3Boz1EGjvbUKhtg3ZadzJi/lLTUtGzL0+VyfJb54794DhtW+rJzTxBxT+LZ/vt+rKtYEuC3kPZtXFizcZvW2cdOnyM1LZ0tS2cyeqA7C/w3q8tu3P2HA8dD2bJsJv7zf2BlwE6SU1IJ+O0ArZ0asXHRDKpaVmBX8HEts/8kNT2dLUu8GT2gBwv8t/wn+zRblnrjP28SKzf9lpG9K4jWTg5s/N90qlauwK6DIdplh0ZktHv5HEZ/24sFqwMys+/8w4FjoWxZPgd/nyms3LDjZbv30dqpMRsXe1PVsiK7gt7v/biVKonGj0/JB+n4nzx5olG9+Ph4lMrP9DqoGmrUqD5HDv8BQETERWxtv1KXPXnyFIeGbZHL5ZQpU4rnzxIAqFevFuXKleFA0C/89vs6rK21u/n7hX/iaFIlY8RVu0IJrj58qi4zkupRtogxyWkKktPlSCQZf+jWpYuQlCYHQJYqR09Huz+pOg2+4nRIxpv4lfPXqF7bJlu5s6sTSqWK08cz3+i3/rSTdUs3AWBRvgxP/o3XKhugYrmyLJk7NcfyO/fuU6lCOYqYmyGVSrGtXZM/L13l/KWrNG1oB8DXDvaER1zQOvv8lSia1q8DQJ3q1ly7cScz/58H2NeugYG+Pgb6+lQqb8GNu/9QrUplEl7IAHiRlIRUT1e77Kv/yb55N0t2DPZ1qmdmlyuTmZ34KjsZqa6W2Veu09S+bkZ2jS+5duN2luxo7Ov8p913/qZaVcvMdsuStW63plQqicaPT8l77/gHDBhATEwMM2bMYP78+Zw7dw53d3fs7Oxo0aIFa9euRaFQcObMGWbMmEFMTAz16tXj6dOnPH78mNGjR+Ps7EydOnVo2bIle/bs0Wo//vjjD9q1a4ednR0DBgxg2rRpTJo0CYBJkyYxcuRIWrVqRaNGjXj06BEXLlygb9++NG3alNq1a9OjRw+uXLkCwMCBA/H29s62fXd3dzZu3Ph2vyzAzNyM5wmJ6ucKhQLdLP9YCoWCIV59ORayi927gwCIjf2X/y3wo22bXiz0XcVP6xZplS1LS8fUIPMyuroSCfIsb8RlihjTxS+Ynv6HcW9QFYAiRgaE3Ymly6pgNp6OolO9L7TKNjEzQZYgUz9XKpXqdlex+YLWnVuwZsHPOdZTKpWs2rGE7gPcOH0sXKtsgBbfNEVPL+fMp0wmw9TEJHM/jY1IfCFDlpSEqamJetkLmSzHupqSJSVjamKsfq6jo4NcoQDgyy8q8eflv5AlJfMsIZGLV2+QnJJKmVIl2Bp4iE6DxnMq4hItHbW7h3NGdubUXPbsivx5+Xpm9rWbGdkli7N172E6DZr4Mrvh+2l35Mt2P0/k4rWX7S5Zgq17guk0cCynIi7Q0rGRVtmaUqk0f3xK3nvHv27dOsqVK4e3tzfdu3enf//+dOjQgfDwcFasWMHWrVtZv349DRs2xNvbm3LlynHhwgWKFSvG1KlTMTIy4sCBA5w/fx53d3dmzJiBLJ//ZP/88w/Dhw9n8ODBnDlzht69e7Nr165sdUJDQ/Hz8+PgwYMULVoULy8v2rZty4kTJwgPD6ds2bLMmzcPgC5duhAUFER6ejqQcVzi8uXLtG/f/q1/X4kJiZiZmqqf6+jooHj5z/DKmtUBVLVqSJMmDXB0dOD8+Uj27TsMQFjYOcqVs0AbJvpSZC9H75Ax5/9qBB966yFxicnsH+lK8Oh2hFyP4fKDJ6w5cZV+jauxa1hr/Ho7Mn7naa2yZYkyjE0zOwGJRKJud9turShlURK/nUto1701vQb3oFGzBuq6w7qPZlDn4fisnaVV9uuYmJiQlJSUuZ9JyZibmWBibExSUrJ6WdbXLN8ZxkbIkpPVz5UqFXov3/SsKpXHvUMrhk7xYcGazdSuVpVi5mYsWruF2eO92L12IZOG9mWy7yrts5Myb4iuVCn/k92SoVN9WeC/hdrVqmRk/7SV2eOGsHutL5OG9mHygtVvkZ1HuytXwL1Ta4b+MJcFawIy2l3EjEX+m5k9YRi7f17EpGH9meyzQqtsTYmpnndg7969VK9eHXd3d6RSKTY2Nnh5ebFz585c68+cOZOpU6eir69PbGwsJiYmJCcn8/x5/g7g7du3j1q1atGhQwf09PRwdnamRYsW2erUrVsXKysrzM3N0dPTY/v27fTs2RO5XM7Dhw8pWrQosbGxADRv3hyFQsHJkycB2L17N46OjhQvXlyL30p24WF/0rJVMwDs7ety9WrmnLm1tRW/bPUDID09ndS0NJRKFT9MHsV3wwcAUOur6ty/H6NVdt1KJTl16yEAkdFPsC5dRF1mbqiPgVQXfV0dDPR0MTOUkpiSjrmhvvpTQnETA16kpmuVfSniCk2cM0attWxrcPt65nTH8tmr6d/OC6+uo9i3I5hf/LcTFnKWfsM9aOPWEoCUpBQUinc/TWhlWZG/o2N4npBIeno6f166Qp1a1alXuwYnwiIAOBkegW2dmlpn1Kv5JSfPZhwzufTXTawtM09uiH+WwNOERAIW/8ikYZ7E/vuEqpYVMTc1UY+WS5Uopp7+yHd2jS85GfGa7OeJBCyawaShfYn9Nz5LtlFmdqKW2TVtOHk2Y4rs0rUbWH9R6T/ZCQQsncWkYf1ftrsS5mbvpt2aUih1NH58Sj7o6ZxPnjyhfPny2ZZVqFCBmJjcO6ro6GgWLlzI3bt3qVixIpaWlgD5Pg4QGxtL2bJlc+TGxcWpn5csWVL9s66uLmfPnmXIkCHIZDKsrKyQSqWoXn6eMzAwoG3btgQGBuLs7MyePXvU00ZvKzDwIM4uTTly7FckEglDh0xg+IiB3LnzNwf2H+Hy5b84FrILlUrF4UMhnDp1hitX/uKndYtp3fob5HI5XoPHa5XtXK084Xdi6bvuKKjAu6M9m8KiqFjclGY25Qm/+4g+Px9FRyKhbqWSNLIqQ9XSRfDeG8GOc7eQK1RMb1dfq+yQoBM0dKzPz4EZI9eZY+fTa3B3ou894MSh3E8MCNx2gB+XTqajuys6ujrMHDtPq+zc7D90nKTkZLp1bMvEEYMYPGYKKpWKzq4tKVOqJD06uzJl9v/oM3QcUj0pvj9O1DrLpYk9Yecv03v0dFQqmDVuCBt/3U+l8mVo5mBH9MPH9Bw+BameHmMHeaCrq8MP3/Vj7or1KJRKVCqYMlzzkyKyZ9d/mf0jKlTMGjuEjb8doFK5MjRzsCU69jE9R0xDqqfL2EHuGdnD+jJ35caX2SqmDO+nXXbTBoSdj6T3yKmoVCpmTRjGxl/3UamcBc0avWz3sB+QSvUYO7h3RvbwAcxd/nNmu0cM1CpbU5/YDI7GJCrV+5+dcnZ2Zvjw4Tx+/JijR49mG+Fv27YNf39/jh07xq5du1ixYgXHjh0jPT0dBwcHxowZg4eHBxKJhCtXruDm5sbRo0epUKECNjY2BAQE0LDh6+cYV69eTUhICNu2ZZ55MW7cOKRSKfPnz1d32vPnzwcgMjKSXr16sW3bNmrVqgVkTFlt3ryZY8eOqev06dMHf39/Ro8ezYkTJ5BKNb/NnKmxdnPh70JB3nrRccIfBZYtbr1YAAr41ov6Feu81fqny7ppXLfxw9/eKutD+iCfT6RSKYmJibi6unLjxg22bt1Keno6UVFR+Pv706lTJwD09fVJSkpCLpeTlpZGSkoKRkZGSCQSYmJiWLAg4zRFuVz+urgcOnTowLVr19izZw8KhYLQ0FAOHjyYZ/3nz5+jo6ODoaEhABcvXiQgIEA9pw9Qu3ZtKlSowPz582nXrl2+On1BED4N4qyet+Dm5sbixYvx8/Pjp59+Ys+ePTg4ODBkyBDc3Nz47ruMc7bt7e0pXrw49vb2PH78mLlz57Jy5Urq1auHp6cnTZo0oXjx4ty6dStf+eXKlWPJkiWsWrUKe3t71q9fT6NGjfLsrJs2bUqvXr3w8PDA3t6emTNn4uHhQXx8PPHxmacMdu7cmWvXrtGlSxftfzmCIHy0lPl4fEo+yFRPQXv48CHPnz+nWrVq6mUjR47kiy++YMyYMVpvNzg4mNWrV7N79+58ryumej48MdVTAD7xqZ4TFt00rusYm/tJKh+jT+tQtJaePHmCu7s7169fB+DcuXOcPHkSR0dHrbYXHx/PX3/9hb+/Px4eHu9yVwVB+IjIVRKNH5+Sz+IibU2aNMl2rvV/hYaGMn78eIYPH86TJ0+wsLBgxowZ2NnZaZV35coVRowYgbOzs5jmEYTPmIpPq0PX1GfR8WtyHSAPD493Njp3dHTk0qVLb64oCMIn7VObu9fUZ9HxC4IgvA9ixC8IglDIiBG/IAhCIaMQI35BEITC5TO986Lo+AVBEPKiFCN+4V1KU2h3Fct3QRUdXWDZSYrUAssuyC9RSUy0uy3ju6CM1+5qre+Ebv4ur/Kx+Vy/3So6fkEQhDyIg7uCIAiFjFIipnoEQRAKFcWbq3ySCsW1egRBELShlGj+yI+4uDi8vLyws7OjSZMmrFiR9y0kjxw5QqdOnbCzs8PV1VV9TxDIuCf0xIkTadCgAQ0aNGDmzJnZLh+fF9HxC4Ig5EGJRONHfowZM4ZixYoRGhrKhg0b+O2339i3b1+OeidOnGDixIl8//33nDt3juHDhzNy5Ej1bWBnzZrFkydPOHr0KHv27OH8+fOsW7fujfmi4xcEQciDKh+PhIQEoqOjczwSEhKybfPvv//m7NmzjBs3DkNDQ6ytrfH09GTLli058jdt2oSnpyeNGjVCIpHQpk0bduzYgampKSkpKezbt4+RI0diZmZG2bJl+e6773Ldzn+JOX5BEIQ85GcKZ+PGjblO2QwfPpwRI0aon9+8eZOiRYtmu8+3lZUVUVFROda9cuUKDg4ODBgwgKtXr1KpUiXGjx+Pqakp169fJz09napVq2bbzqNHj3j27BlFi+Z9CrHo+AVBEPKQn9M5PT096dy5c47l5ubm2Z7LZDKMjIyyLTMyMiIlJSXHus+fPycgIIDly5dTvXp1du/ejZeXF4GBgbx48UK9btbtALluKyvR8QuCIORBkY8Rv7m5eY5OPjfGxsY5Oubk5GRMTU1z1DUwMKBbt27Url0bgG7durF582ZOnDhBvXr1gIxO3tjYWL0dINdtZSXm+AVBEPLwPu65a21tzdOnT7Pdv/v27dvZpmxeqVKlCqmp2b/trlBknGRqaWmJVCrlzp072bZjYWEhOn5BEARtvY+O39LSknr16uHr60tSUhK3bt0iICAg12miHj16sGXLFiIiIlAoFGzfvp0HDx7QvHlzjI2NadWqFYsXL+bZs2fExsayatWqXLfzX2KqR0tHjhxhxYoV3L9/HwsLC8aNG4ezs/Nbb1cikbB8+Vxqf1WD1NQ0vIZO4Pbte+pyLy9P+vbphkoFc+Yu5sCBo+oyG5sqnDq5lwoV6+UYJWiYjrRlH3RKVwSFnLSg9aiePVaX6jVojV71hqhUKuRh+1DcPA9SffTbeyExNIH0VFL3rYXkRK3aPc1nIjY1rUlLTWPG2Ln8cy86Rx2/LYs4FnyCHQG/q5e7tHGiVQcXJg6drkWbMyiVSmYvX0fUnX/Ql+rhPWYwlcpbqMt/3h5I0PHTmBgbMaB7e5wcbHn4OI4ffFaiUkERM1N8fhiOkaGBVvmRV6+zyG8dG1b4Zlseciocv9G44V8AACAASURBVPW/oKerS+d2LenaoQ0pqalM8l5A/NNnmBgbMWfqOIoX0+5aQEqlkjl+m4m6ex99qZQfR3hSqVwZdfm6Xw8QdOIsJsaG9O/SBqcGdfBZu5WoO/cBiHv6HDNTY7YsnKJd9soAou7+k5E9akD27J37CfojHBMjQ/p3dcWpYV181mwh6s4/mdkmxmxZrP3r/ibv61a6y5YtY+bMmXzzzTdIpVJ69epFt27diImJwdXVlbVr11K/fn26dcu42fuPP/5ITEwMlpaWrF69mjJlMn5P3t7ezJkzh7Zt26JQKGjfvj3Dhw9/Y77o+LXw6tzalStX4uDgQHBwMCNHjuTIkSNYWFi8eQOv0bFDawwNDHB06kiDBrb4+kzDretAAEqUKIbXkL7Ut2+FoaEBly4e58CBBgCYmZni4zOd1NQ0rbN1v7RFoicldfMcdMpZIXXuSdquZRmFBkbo2TUnZc33IDXAsL83ipvn0avjhDL2HvLTgejWaoK0cXvSj/6S72yXNk4YGOjj4fotte1qMcF7FCM8J2SrM/IHL4oUyz6HOmn2WJo0a8j1qze1bjfAsdPnSE1LZ8vSmVz66yYL/Dez3Hs8ADfu/sOB46H8smwWAH1Gz6BB3ZoE/HaA1k6N6NmhJcvWb2dX8HE8OrXOd/a6LTvZG3wsx5tGulyOzzJ/tv209P/t3XdYFEcDx/Hv0aXFhgKCYEGxgQKCokZji4pEwWCJIooFW+wtsdfY4mvsUWPUBFOMRlEsQSNKUGwoBBUUK4pYUarUff8gOSA2QI7jYD7vw/Pkdvb2N8OLc3Ozs7voVtBhwIhJtGvlhH9AIFZ1LBk9ZAAHjwby7faf+WL8iKK1O+QiaekZ/LhiBmGRN1ix9VdWz8xZgXLt9j0OnjiD79czc9o9ZTGONtZMG9ZPXj+vaUuYM8araNmnQ0nLyODHlbMJi4xmxZafWD17fE72rRgOBp6Wd+qekxbiaNuAaT79c7MnL2LO2MFFyi4oRd2rp1q1aq9dAWRqasrFixfzbfPw8JB/APyXvr4+X331VaHzVW6qJzw8HA8PD+zs7OjTpw/Lli3D09OTNWvW4O3tjbu7O05OToSHh3Pjxg18fHxo164dNjY2uLq6EhQUBMDs2bMZPnx4vmNPnjyZxYsXv7MOb1tb+76cWzXnjz8CATh7NhQ7O1t52dOn8dg7dCYzMxNj42q8eJG7PnjD+qXMnrWElJTUImermVmRdetvALJjb6JmbJlbmJGO9OIpaGoj09IGKee+hZnnA8g8vR8AmWEVpOQXRcq2c7Llr+MhAIRfiKCRrXW+8s7d2yNlZxN07HS+7ZfOhbNgWv5RclGERkTR2iHnd23bwIor13LnTW/evU9zm4Zoa2mhraVFzRrGXLt1F+s6FiQkJQOQlJKCpoZ6kbLNTU1YtXjmK9tv3o6hppkpHxgaoKmpiZ1NIy6EXSY07DKtnewBaNOiOSHnLr7y3oK6eOU6rewbA2BrXYcr12/Ly27FPMChSX20tTTR1tLEwrQ61/J8C/vpwDGcmzWinqVZ0bIvX6OVfZN/suty5fqtPNmxODSxlv/Oc7JjcrP9juJs15h6tcyLlF1QWYX4USUq1fEnJCQwfPhwOnXqxJkzZ5g2bRq7du2Sl4eEhPDll19y7NgxGjduzNixY7G2tiYgIIDz58/TsmVLZs2aBYC7uzvBwcHyEyzJyckcPXq0QPNjERER6Ovr4+3tjZOTEx4eHiQmJhZLx29oYMCLhNypkqysLNTV1fO9HjlyEEEn/dizxx+AWTMncujQn4T/ffW9smVaFZDS8nxwSNkgy/0TkRKfUWHoInS85pJ54Wie/SS0+05F074jWTfDi5StZ6BHYkKS/HV2Vra83XWta9PNvTNrlm565X2H9x1Fkt7/5rnJKano6+nKX6upqZH5z0m0erVqcuHvqySnpPI8IZFLl6+R+jKN6kZV+MnvD3oOm8xf58Lo/GGLImV3+qg1GhqvfvlOTk5GX09P/lpPtwKJSckkp6Sgr68n35aUnFykXICklJfo676+3VaWNQi9fO2fdidxKTKa1H+mEDMyMtl1+ARebh+/R3Yq+rq5SxHzZ5sTGhGVm301mtSXebIPHcerV9ciZxeUom7ZoGwqNdVz/PhxtLW1GTZsGDKZDDs7O3r37k14eE5nY25ujoODg3z/f+fCZDIZsbGxGBoayi91btq0KRYWFvj7++Pp6cmRI0ewsLCgQYMG76zH29bWmpu/3wgkITERA/3cf+xqamrys/j/2rBhG1u2+LJ//w+0betMv8/cuX/vAYMG9cXY2IiD/r506PhpobOl9FRkWjq5G2SynM4fUK/dBJneB6RuzJl+0e49iez718l+kDNKS/t5GbLKxmh/OoGXm6YVOjs5MRk9/dwOSJan3T08ulHdxIitu9dRw9yEjIxMYmMeyL8hFAc93Qokp+Z+6GVLEhr/fPDUrlmDfp98zMgZSzE3rY6NdV0qGRow6+uNLJw8glYOtpw8E8qXy9azfmHh2/7GOunpkZKSIn+dnJKKoYEeerq68m92ySmpGLzHgENfV4eU1NylhfnabW5KX5cOjJq7CnOTajSpV5tKhgYAhIRdwb5RPQzyfFgWPrtC/uzsvL9zU/q6dmTU7K8xN61Ok/p5si9dxr5x/ffKLqiyeltmlRrxP3z4EGNjY2R5bpVqZpb7NdPIyCjf/pGRkXh4eNCmTRumT59OZGRkvtFhz5498fPzA2Dv3r0FGu1D/rW1mpqaeHh4ULNmTU6ePPk+zQPg9KnzdOmSc5LY0dGOiMuR8rJ69Wrz6y+bAcjIyCAtLZ3s7GwaNmxNp84edOrsQVzcY7q59C9Sdva966jXzlkvrGZaG+lx7td66WUyZGZAViZkZeZ8M9DWRaOFC+qNWubslJEu/6AorItnw/mwgzMANvaNuX41Wl729YK19Os6hMHuo9j7iz/bN+4s1k4foFmjegSdvQRA2NXrWFnmfoA/e55AfEIiO/43l+mjvIh7/JS6luYY6uvJvyUYVakkn/YpLrUtzblzL5YXCYlkZGRwISwC28YNaGbTkJOnzwEQFHIOO9tGRc5o2qAuQedzBk5hkTewsqghL3v2IpHnCYlsX/YF04b3I+7JM+rWzCkPuXSF1v9M0xQ5u6FVnuxorPJMGT17kcDzhCS2r5jJNJ/+xD1+Rl2LnPKQi5dp7WDzXtkFpYhVPaWBSo34TUxMiI2NRZIkeef/4MEDeXneD4RHjx4xbtw41q5dK19tc+TIEQICAuT79OzZk1WrVnHp0iUuXrzIqlWrClSPt62tfV979x2iQ8c2nAjci0wmY9jwiYwbN4wbN25z4EAA4eFXCDrphyRJHDlynKCg4usAs66FombZCO0BOSs00g9+h0bzzkjxj8iKvkR23C20PWeCJJF97zrZty+T/SgGbZehaNh8CDI10g9+V6TsowcDadnWkR8PbEYmkzFz3AK8fPpx9/Y9jh8JKrY2vkmHVs05Hfo3A8bPRpJgwSQftv/mT80a1WnXwp57Dx7Rd8wMNDU0mDisP+rqanwxehCL135PVnY2kgQzxhTPiUb/P46TkpqKR49uTP18GMMnzECSJNxcOlPdqCp93FyYsfBrPEdOQlNDk2Vzpxa93S3tCLl0Bc8pi5EkiQXjvNmx9wjmJtVp52jLvbgn9JuwAE1NDSYO9kBdPWesePt+HK7tnd+rnR2c7Qm5eBnPSQtysicMZceew5ibVqOdUzPuxT2i37i5aGqoM3FIn/zZHVq9V3ZBldUncMmk4pggLSHJycl06tQJLy8vvL29iYqKYujQoVhZWeHo6MjZs2f54YcfALh58yZdu3Zl+/bttGjRgujoaCZOnEhUVBQRERFoamoCMGzYMJ48eYKJiQnr168vUD127drFV199xbfffoudnR2//fYbS5Ys4fDhw/JlVu+ipV20E2LF4fn8TkrLbr7yitKyL57doLTs8vvoReWOLbXrFO28y7+WWQwo8L5T7/z4XlklSaVG/Hp6eqxbt4758+ezceNG6tevT+vWrfNdAfev2rVrM3XqVCZPnkxqairGxsb07t2bZcuWER0dLZ/Ld3d3Z/z48YwePbrA9XjX2lpBEMoGVVutU1Aq1fHHx8cD8PvvuRfvLF26FEmS8t397l9DhgxhyJAh+bZ5eeVfc2xmZkaVKlVo27ZtoerytrW1giCUDdlldLJHpU7uZmZm4unpyenTOWu5o6Oj2b9/P+3atSv0sZKSkoiKimL16tV4eHjIp34EQRD+JU7ulgJGRkasWLGChQsXEhsbS6VKlRg8eDCurq6FPtaDBw/o27cvNjY2+S7kOnr0KFOmTHnj+zp27Mjy5cuLVH9BEFRL2Rzvq1jHD9ClSxe6dCn8ZfH/ZWVl9cql0ZDTsb9uuyAI5Y+qjeQLSuU6fkEQhJKSKSubY37R8QuCILxB2ez2RccvCILwRmKqRxAEoZwpq8s5RccvCILwBmWz2xcdvyAIwhuJqR6hWCn1Fkl57oFe0rTVlHihXBHvHFoclHm/HLXKpkrLzn7x6N07lWJZZXTMLzp+QRCENxAjfkEQhHJGEiN+QRCE8kWM+AVBEMoZsZxTEAShnCmb3b7o+AVBEN4os4x2/aLjFwRBeANxclcQBKGcESd3BUEQyhkx4hcEQShnxIhfEAShnMlS5q1VFEh0/IIgCG8g1vELci4uLsTG5r/pVkpKChMnTsTHx+e9ji2TyVi75itsbBqSlpaGz4gp3LhxW14+coQXAwf2RpIkFi5axcGDR+Vl9evXIfivA9Qwa0paWlqhs7MlicWBUVx7koiWuhqz2zegZkVdefmO0Dscvv4QmQyG2FvSvk41JEni423B1Pwg58ZvNsYfMNa5bpHa/cWSSdRrWJf09AwWTFpCzO37r+yz+sflBB4JYveOfegb6LFw7Wz0DHTR1NRk5dw1hF+4XOhsgOzsbBau+Z6oW3fR0tRk3vih1KxhLC//7pf9HAo8hZ5uBbw9utO2hR0PHj3hi2UbkCSJDwz0WTp9NBV0tIuUvWjDj0TdikFLU5O5n3tR07S6vHzrbwc5dPIsero6DHbvSltHW5Zu/omomzEAPIl/gYG+Lr4rZhSp7eGXI1m5YSvb1i7Ltz3wrxA2fL8TDXV13Lp35tNPuvIyLY3p85bzLP45eroVWDRzEpUrVSxSbnZ2NovW7ZD/zueO887f7l3+HDoRgl4FHQZ/6kJbp6Ys/daXqJt3c9utp4vv/2YXKb8gxBy/IOfv75/v9apVqwgMDGTAgAHvfewePbqgo6NNmw8/wcnRjmXLZtOrlzcAVapUwmeEFw4OndHR0SY8LJDa/3T8Bgb6LFs6h7S09CJnH7/5mPSsbHZ4NCc87gUrg6+zysUWgMS0DH4Kj8HP05nUjCz6/HKW9nWqEfMilQZGBnzT3fa92v1R1zZoaWsxyHUETewaMWHOGCYO/iLfPqOnD8OwoqH89QCfPpz96zw7N+/Coo45izfMpX/nIUXK//PUBdIyMvBdNY+wq9dZvsmXNfMmAXDt1l0OHj/FztXzAPCcMA/Hpo3YsecQXdq2oK9rJ1Z//yt7jgTSv8fHhc8OuUhaegY/rphBWOQNVmz9ldUzP8/Jvn2PgyfO4Pv1zJzsKYtxtLFm2rB+AGRkZuI1bQlzxngVqd1bfXex//Cfr3xgZWRmsnT1Jn7e8g26FXQYMGIS7Vo54R8QiFUdS0YPGcDBo4F8u/1nvhg/okjZf54OJS0jgx9XziYsMpoVW35i9ezxOe2+FcPBwNPyTt1z0kIcbRswzad/brsnL2LO2MFFyi6osjrHr6bsChRWeHg4Hh4e2NnZ0adPH5YtW4anpydr1qzB29sbd3d3nJycCA8P58aNG/j4+NCuXTtsbGxwdXUlKCgIgNmzZzN8+PB8x548eTKLFy8uVH1CQkLYvn0733zzDXp6eu/dvlbOjhz54zgAZ86GYm9nIy97+jQee/tOZGZmYmxcjRcvXsjLNmxYxqzZS0hJSS1y9sXY5zjXrAzkjNyvPEqUl+loqGNioENqRhapmVnyP5yrjxN5lJzGsN8vMGb/JW7HJxcpu6mjDaeOnwHg79DLNLS1zlfewaUd2dkSp/4MkW/7cdOv7P5hHwDq6hqkvyz6h17o5ShaO+R8eNk2sOLK9Vvyspt3Y2lu2wBtLS20tbSoaVqda7fuYl3HgoTEnPYmpaSiqa5epOyLV67Tyr5xTrZ1Ha5cvy0vuxXzAIcm9dHW0kRbSxML0+pcu31PXv7TgWM4N2tEPUuzImWbm5qwavHMV7bfvB1DTTNTPjA0QFNTEzubRlwIu0xo2GVaO9kD0KZFc0LOXSxSLsDFy9doZd8EAFvruvl+57diYnFoYi3/nee0O0Ze/pPfUZztGlOvlnmR8wsiG6nAP6pEpTr+hIQEhg8fTqdOnThz5gzTpk1j165d8vKQkBC+/PJLjh07RuPGjRk7dizW1tYEBARw/vx5WrZsyaxZswBwd3cnODiYZ8+eAZCcnMzRo0dxc3MrcH2ysrKYM2cOo0ePxsLColjaaGioz4sXuR1uVlY26nk6lKysLEaNHMRfQfvZvSfnm8esWRM5dOgY4eFX3is7OSMLfe3cL4HqMsjMzh3zVNfXodfOEPr9cpZ+tjn/4KrqauFtb8FmN3uG2FsyI6BoUy16+nokJeZ+aGRl57a7Tv1adHXvxIZlW/K9JykhibSX6VQxqszCtbNY89W3RcoGSE5JRV8v9zkFampqZGZlAVCvljkX/o4kOSWV5wmJXLpyndSXaVSvWpmf9gfQc9hU/joXRucPnYqUnZTyEn3d3Cm1vNlWljUIvXztn+wkLkVGk/rPNF5GRia7Dp/Ay63w3zL+1emj1mhovPrFPzk5Gf08Axk93QokJiWTnJKCvr6efFtSctE+6CHnw1Jf9/W/cytLc0IjonLbfTWa1Jd52n3oOF69uhY5u6CkQvxPlajUVM/x48fR1tZm2LBhyGQy7Ozs6N27N+Hh4QCYm5vj4OAg33/jxo1Ur14dmUxGbGwshoaGxMXFAdC0aVMsLCzw9/fH09OTI0eOYGFhQYMGDQpcn/3795Oamoqnp2extTEhIQkDA335azU1NbL++cfwr/UbtrF5iy8H9v9I27bOfNbPnfv3HzB4UF+MjY04dHAn7Tv0KnS2nqY6Kem5WdkSaKjljA2C7z7lSUoaBwY6AzDK7xJNTT6gYTVDNNRkADQzrcijpDQkSUImkxUqOzkpGT29PJ2fTCZvd3ePLhgZG/Htb6sxNTcmIz2TBzFxnDp+hrrWtflq4zz+N38doacvFbrN8rbrViA55WWetmej8c8HT+2aNej3SWdGzlyGuWl1bKzrUMnQgFkrN7Fwkg+tHGw4eeYiXy7fyPoFUwqdra+rQ0pq3mwpN9vclL4uHRg1dxXmJtVoUq82lQwNAAgJu4J9o3oY5Pm9FRc9PT1SUlLkr5NTUjE00ENPV1f+rTI5JRUDff03HeKd9HUr5G93dp521zSlr2tHRs3+GnPT6jSpn6fdly5j37i+Qtr9X2V1VY9KjfgfPnyIsbFxvk7FzCz3K66RkVG+/SMjI/Hw8KBNmzZMnz6dyMjIfE++6tmzJ35+fgDs3bu3UKN9gF9//ZXevXujrV34E3pvcur0Obp2aQ+Ak6MdERFX5WX16tXh1183A5CRkUFaWhrZ2dk0aNiajp086NjJg7i4x3Tt9lmRspuaVOSvO08BCI97Qd0quf+oDbU10NZQR0tdDW0NdQy0NUhMy2TTuVv4huV8BY96koiJgU6hO32AS+f+plWHFgA0sWtEdORNedk3Czfg5TKc4b0+Z/8vh/hx08+cOn6GWvUsWbp5AV+OmpdvCqgomjWsR9C5nA+OsKvXsbLMnUJ49jyB+BeJ7Fg5h+kjBxL3+Bl1Lc0x1NeTf0swqlJJPu1TWE0b1CXofM7gJSzyBlYWNXKzXyTyPCGR7cu+YNrwfsQ9eUbdmjnlIZeu0PqfqZLiVtvSnDv3YnmRkEhGRgYXwiKwbdyAZjYNOXn6HABBIeews21U5IymDa3ytDsaqzzTVc9eJPA8IYntK2Yyzad/zu/cIqc85OJlWjvYvPaYxa2sTvWo1IjfxMSE2NjYfCPKBw8eyMvzdjiPHj1i3LhxrF27lvbtczrSI0eOEBAQIN+nZ8+erFq1ikuXLnHx4kVWrVpV4Lo8efKE0NBQli5d+r7Nymfv3kN07PAhJ0/sQyaTMXTYBMaPG070jVscOBBAePgV/grajyRJHD7yJ0FB79fh5dW+jhEhMc/w+u08kiQxr2NDfrh4F/OKFWhXy4gzMfEM/O08MnJG9y3MK9OomiEzAi4TdPsJGmoy5nVsWKTs4wdP0uLD5nzvtwGZTMbcCYvp79OHmFv3OPlH8Gvf8/kXPmhrazFlwTggZ+rnvyeEC6pDKwdOh/7NgPFzkZBYMNGH7bsPUtO0Ou1a2HEv7hF9P5+FpoY6E4f1Q11djS9GDWTxuu1kZWcjSRIzxgwqWnZLO0IuXcFzymIkSWLBOG927D2CuUl12jnaci/uCf0mLEBTU4OJgz1QV88Zr92+H4dre+ciZb6J/x/HSUlNxaNHN6Z+PozhE2YgSRJuLp2pblSVPm4uzFj4NZ4jJ6GpocmyuVOLnNXB2Z6Qi5fxnLQgp90ThrJjz2HMTavRzqkZ9+Ie0W/c3Jzf+ZA++dvdoVVxNfmtyurJXZmk1Ie/Fk5ycjKdOnXCy8sLb29voqKiGDp0KFZWVjg6OnL27Fl++OEHAG7evEnXrl3Zvn07LVq0IDo6mokTJxIVFUVERASamjnPfh02bBhPnjzBxMSE9evXF7guR48eZf78+Zw8ebJIbdHUqvHunRTkxdc9lJbdenG40rJDThf8g724Sekv372TgpTnZ+5q12nxXu/vXtOlwPseuOv/7p1KCZWa6tHT02PdunUcPnwYR0dHFi5cSOvWreWdeF61a9dm6tSpTJ48GXt7e8aNG0evXr3Q0NAgOjpavp+7uztXrlzB3d29UHW5d+8e1atXf/eOgiCoLDHVUwrEx8cD8Pvvv8u3LV26FEmS+Pzzz1/Zf8iQIQwZkn9dt5dX/vXOZmZmVKlShbZt2xaqLoMGDWLQoEGFeo8gCKpFURMiT548YebMmZw7dw4dHR369evHmDFj3vqe4OBghg4dSkBAgPzc5tGjR/n888/R0dGR79exY0eWL1/+1mOpVMefmZmJp6cnmzdvpmXLlkRHR7N//36mTZtW6GMlJSVx//59Vq9ejYeHx2u/NQiCUL5lKWgkP2HCBMzMzAgODiYmJobhw4djaWlJ9+7dX7v/48ePmTZtGtnZ+c86RERE0LVrV1auXFmofJXq+I2MjFixYgULFy4kNjaWSpUqMXjwYFxdXQt9rAcPHtC3b19sbGzyXch19OhRpkx585K8gnyaCoJQNhRmCichIYGEhIRXthsaGmJomHvF+Z07dzh79iz/+9//0NHRwcrKCi8vL3x9fV/b8WdnZzN58mR69+7NunXr8pVFRETg7Fz4E/wq1fEDdOnShS5durz3caysrLh48dWrDjt27Pja7YIglD+FmerZvn07a9eufWX7mDFj8k1FX79+nYoVK1K1alX5ttq1axMVFfXa465fv56KFSu+tuO/fPkykiTx448/kpGRQdu2bZkyZQoffPDBW+uqch2/IAhCSSnMiN/Ly+u11wLlHe1DzurEChUq5NtWoUIFXr58deXX2bNn2bdvH3v27CH5P1dJJyYmUrduXTp27EiPHj1ISEhg2rRpTJkyhU2bNr21rqLjFwRBeIPC3Irhv1M6b6Krq/tKJ5+amor+f66CfvbsGdOnT2flypUYGBi80vEbGBjIl6//e9zJkyfj4eFBUlLSK8fLS6WWcwqCIJSkLEkq8E9BWVlZER8fL79PGMCNGzeoWzf/7cyDgoJ4+vQpQ4cOxcHBAReXnGsKPvnkE/bv38/NmzdZunRpvlu6pKWloaamhpaW1lvrIDp+QRCEN1DEOn5LS0uaNWvGsmXLSElJITo6mh07drwyTdSjRw/CwsI4f/4858+fl98O3s/PD1dXVypWrMiuXbvYsGEDGRkZPHjwgOXLl+Pm5iY6fkEQhKJS1AVcq1evJikpiY8++ohBgwbh4eGBh4cHsbGxNGvWjPPnz7/zGJUrV2bLli2cOnWKFi1a4ObmRuPGjZk9+90PplGpWzaUJRpKvGVDghJv2dB0/lmlZUeEfqe0bCm96M9JUGVqH1RTar5m1drv9f4Wpu0KvG9IbOB7ZZUkcXJXEAThDVTtVgwFJTp+QRCEN1C1B6wUlOj4BUEQ3iBLKps3ZhYdvyAIwhuU1VOgouMXBEF4AzHHLwiCUM6IOX5BEIRyJltM9QiCIJQvYsQvCIJQzohVPYIgCOWMmOoRBEEoZ8RUjyAIQjkjRvxCPj179uTmzZuoq6vLt/3222/UqVPnvY4rk8lYu+YrbG0akpaWxvARU7hx47a8fOQILwYO7A2SxMJFq/A/eFReVr9+HU79dQBTs6akpaUVOjtbklgcGMW1J4loqasxu30DalbUlZfvCL3D4esPkclgiL0l7etUQ5IkPt4WTM0Pcp4oZGP8AWOd674p4p1tn7tsOtaNrEhPz2DGhAXcvXXvlX02/7SKo4dO8vP23WjraLNiwwKqVK1EclIKU8fMIf7p88K3PTubhau3EHXjDlqamsybNIKaNYzl5d/9vJdDx4PR09XFu88ntG1hz4OHT/hi6RokCT4w0GPpl+OooKNdpOxF63YQdesuWpqazB3nTU3T6vLyrbv8OXQiBL0KOgz+1IW2Tk1Z+q0vUTfvAvAk/gUGerr4/u/dd2UsTdn/Cr8cycoNW9m2dlm+7YF/hbDh+51oqKvj1r0zn37SlZdpaUyft5xn8c/R063AopmTP2umegAAIABJREFUqFypYpGz30WM+AW59PR0oqOj8fPzo3bt97v733/16NEFHR1tWn/4CU6OdixfNhv3Xt4AVKlSiREjvLB36IyOjjZ/hwXKO34DA32WL51DWlp6kbOP33xMelY2OzyaEx73gpXB11nlYgtAYloGP4XH4OfpTGpGFn1+OUv7OtWIeZFKAyMDvulu+95t79StHdo6WvTp5o2tfWOmz5vAqIGT8u0z4cuRfFAx93minw36lGtXolmzfBMuPTszauIQFs34utDZfwafIy09A981iwi7co3lG3ewZsFUAK7dvMvBP4PZuXYRAJ5jZ+HYtDE7dh+gS1tn+vb4mNVbf2LPoT/p79a18NmnQ0nLyODHlbMJi4xmxZafWD17fE72rRgOBp6Wd6yekxbiaNuAaT79AcjIzMRr8iLmjB1c6FxlZwNs9d3F/sN/vvKBmZGZydLVm/h5yzfoVtBhwIhJtGvlhH9AIFZ1LBk9ZAAHjwby7faf+WL8iCLnv0uWlPXunVSQyt2PPzw8HA8PD+zs7OjTpw/Lli3D09OTNWvW4O3tjbu7O05OToSHh3Pjxg18fHxo164dNjY2uLq6EhQUBMDs2bMZPnx4vmNPnjyZxYsXv7MOV69eRVtbm1q1ahV7+1o7O3Lkj+MAnDkbir2djbzs6dN47Ow7kZmZibFxNZ6/eCEv27hhGTNnLyElpei3/70Y+xznmpWBnJH7lUeJ8jIdDXVMDHRIzcgiNTNL/odz9XEij5LTGPb7Bcbsv8Tt+OTXHLlg7J2aEnTsNABhFyJo0rRBvvKPXTuQnS1x8tipPO+x5eSfOa9PHAvG+UPHImWHRkTSunlTAGwb1uPKtRvyspt379HctiHaWlpoa2lRs4Yx127ewbquJQlJOe1NSk5FU0P9tcd+l4uXr9HKvklOtnVdrly/JS+7FROLQxNrebaFaXWu3Y6Rl//kdxRnu8bUq2WuctkA5qYmrFo885XtN2/HUNPMlA8MDdDU1MTOphEXwi4TGnaZ1k72ALRp0ZyQcxeLnF0QkiQV+EeVqFTHn5CQwPDhw+nUqRNnzpxh2rRp7Nq1S14eEhLCl19+ybFjx2jcuDFjx47F2tqagIAAzp8/T8uWLZk1axYA7u7uBAcHyx9/lpyczNGjR1/7sOT/ioiIQFdXl4EDB+Lk5IS7uzt//vlnsbTRwFCfhBe5HW5WVna+6aSsrCxGjRxEcNB+9uzJeSLP7FkTOXjoGOHhV94rOzkjC33t3C+B6jLIzM5dzlZdX4deO0Po98tZ+tnm/GOvqquFt70Fm93sGWJvyYyAy0XO1zfQIzExSf46b9utrOvg6v4x3yzZ+Mp7khJy3pOclIKB4ZufM/o2ySmp6OvlTmupqamR+c8j7erVqsmF8Kskp6Ty/EUil65cI/VlGtWrVuGnfYfpOWQif527SOcPWxYpOyklFX3d3Idv5822sjQnNCIqJzshiUtXo0l9mTONl5GRya5Dx/HqVfhvGaUhG6DTR63R0Hh14iE5ORl9PT35az3dCiQmJZOckoK+vp58W1Jy0QcaBaGoB7Eom0pN9Rw/fhxtbW2GDRuGTCbDzs6O3r17Ex4eDoC5uTkODg7y/Tdu3Ej16tWRyWTExsZiaGhIXFwcAE2bNsXCwgJ/f388PT05cuQIFhYWNGjQ4LXZeUmSRJMmTZg8eTJmZmYEBAQwbtw4fvjhB5o2bfpebUxMSELfILfzUlNTy/dMTYD1G7axeYsv/vt/pF1bZz7r5879+w/wHtQXY2MjDh/cyUcdehU6W09TnZT03KxsCTTUcsYGwXef8iQljQMDnQEY5XeJpiYf0LCaIRpqMgCamVbkUVIakiQhk8kKnZ+UmIyeft7OVyZve8/eLlQ3qcaO3zdSw9yEjIwM7sfE/vOefzoCfV0SXiS99tjvbLtuBZLzfFvKliQ0/vnQqW1hRr+eXRj5xWLMaxhjY12XSh8YMGv5BhZOGUWr5k05GRLKl0vXsn7xF4XO1tetQEpq7sO3s7PzZNc0pa9rR0bN/hpz0+o0qV+bSoYGAIRcuox94/oY5PnAUqXst9HT0yMlJUX+OjklFUMDPfR0deXfapNTUjF4ywPFi4OqjeQLSqVG/A8fPsTY2Dhfp2JmZib/byMjo3z7R0ZG4uHhQZs2bZg+fTqRkZH5/o/s2bMnfn5+AOzdu7dAo32AAQMGsH79emrXro2WlhYuLi44Oztz5MiR92keAMGnz9G1S3sAnBztiIi4Ki+rV68Ou37dDEBGRgZpaWlkZ2dj3bA1HTp50KGTB3Fxj+nS7bMiZTc1qchfd54CEB73grpVcv9RGWproK2hjpa6Gtoa6hhoa5CYlsmmc7fwDcv5+h/1JBETA50idfoAF86G0bZjKwBs7Rtz7Wq0vGz5/NV4dBmEZ08ffv/5AN9v2EnQn6cJzfOeth1acT6kaF/9mzWqT9DZnPeGXbmGVa2a8rJnzxOIf5HAjm8WMH3UYOIeP6WuZU0MDfTk3xKMqlSST/sUVtOGVgSdzxm8hEVGY2WZ+zf97EUCzxOS2L5iJtN8+hP3+Bl1LXLKQy5eprWDzWuPqQrZb1Pb0pw792J5kZBIRkYGF8IisG3cgGY2DTl5+hwAQSHnsLNtpLA6QM4AoKA/qkSlRvwmJibExsbmG1E+ePBAXp63w3n06BHjxo1j7dq1tG+f05EeOXKEgIAA+T49e/Zk1apVXLp0iYsXL7Jq1aoC1cPX1xczMzPatm0r35aWloa2duFXdPzX3r2H6NjhQ4JO7EMmkzFk2ATGjxtO9I1bHDgQQHj4FYKD9iNJEoeP/MnJoJD3zvxX+zpGhMQ8w+u380iSxLyODfnh4l3MK1agXS0jzsTEM/C388jIGd23MK9Mo2qGzAi4TNDtJ2ioyZjXsWGR8wP8j9OqrRM/+3+HTCbji7HzGDyiP3duxfDnkZOvfc/Obb+xdO08fjqwhfT0DCaNeHW+uCA6tHbkdGg4A8bORJIkFkwZxfbfDlDT1Jh2Le259+ARfUd9gaamBhOHD0BdXY0vxnizeM13ZGVnI0kw4/MhRct2tifk4mU8Jy3IyZ4wlB17DmNuWo12Ts24F/eIfuPmoqmhzsQhfVBXzxmv3b4fh2uHVkXKLA3Zr+P/x3FSUlPx6NGNqZ8PY/iEGUiShJtLZ6obVaWPmwszFn6N58hJaGposmzu1GKvQ15ldVWPSj1zNzk5mU6dOuHl5YW3tzdRUVEMHToUKysrHB0dOXv2LD/88AMAN2/epGvXrmzfvp0WLVoQHR3NxIkTiYqKIiIiAk1NTQCGDRvGkydPMDExYf369QWqx//+9z8OHDjAd999h5mZGfv27WP+/Pn4+flhYWFRoGOIZ+6WPPHM3ZKn6s/cNfqgfoH3ffwi6r2ySpJKjfj19PRYt24d8+fPZ+PGjdSvX5/WrVvLT9DmVbt2baZOncrkyZNJTU3F2NiY3r17s2zZMqKjo+Vz+e7u7owfP57Ro0cXuB5jxowhMzOTgQMHkpCQQJ06ddi0aVOBO31BEFSDCo2LC0WlRvzx8fHcvn2bZs2aybctXbqUR48e8fXXhV+7DfD333/j4+PDiRMn5N8CSoIY8Zc8MeIveao+4q9sYFXgfZ8lXn+vrJKkUid3MzMz8fT05PTpnLXe0dHR7N+/n3bt2hX6WElJSURFRbF69Wo8PDxKtNMXBEE1lNV1/Co11WNkZMSKFStYuHAhsbGxVKpUicGDB+Pq6lroYz148IC+fftiY2OT70Kuo0ePMmXKlDe+r2PHjixfvrxI9RcEQbWo2vr8glKpqZ6yREz1lDwx1VPyVH2qx1Cv4O9PSL75XlklSaVG/IIgCCVJPIhFEAShnFG1C7MKSnT8giAIb1BWZ8JFxy8IgvAGZfXKXdHxC4IgvIEY8QuCIJQzZXWOXyznFARBKGdU6spdQRAE4f2Jjl8QBKGcER2/IAhCOSM6fkEQhHJGdPyCIAjljOj4BUEQyhnR8QuCIJQzouMXBEEoZ0THLwiCUM6Ijl8QBKGcER2/IAhCOSNu0lbKnTt37p37NG/evARqohxRUVHUr1+/xHN/+OEHXF1dqVixYonmPnz4EAMDA3R1dbl//z4nTpwAcp71XK2aYh9juGnTJjw9PalQoYJCc17n5s2b1K6d+5jD8PBwDh8+jI6ODm5ubpibm5d4ncoycZO2Us7a2vqt5TKZjKtXr5ZQbcDR0ZGzZ0vuubnNmjXD0tISNzc3XF1dqVSpUonkfvbZZ0RERPDhhx/i7u5O27ZtUVdXV2jm8ePHGTduHL/++isJCQn4+PhgYWFBVlYWsbGxfPvttzg4OCgs39ramoYNG/LNN9+UeEdrZ2dHaGgokPt7cHZ2Ji0tjUuXLrF582aFtr28ER2/8FoDBw587fYLFy5gb28PwI4dOxRej+TkZA4dOsS+ffsICwvjww8/xM3NjXbt2im8I46JiWHv3r34+fmRkpJC9+7dcXNze+eHcVG5uroyevRounTpQp8+ffj000/x8PAA4JdffuGXX35hz549CsmGnA/ZQYMGsX37dj7//HP69++PlpaWwvL+m33x4kUAPv30U7y9venWrRsAu3fv5ueff2bXrl0lUpfyQHT8KiQpKYkjR44QGxuLt7c3V69eVdgoaMqUKfj7+9O3b1+MjIzk27/99lt8fHwAGDlypEKy3yQ2NpZDhw7h5+fH48eP+eSTT+jbty+WlpYKzz579ixLlizh6tWrNGjQgP79++Pu7o5MJiu2DAcHB86fPw+Ak5MTp06dkn+4ZWdn07x5cy5cuFBsef/176g7JCSEuXPn8vLlS/r06YOrqytmZmYKy82bDdCiRQv++usvNDRyZqKzsrJwcHCQfzAI70+c3FUR0dHRdOnShW3btrF161YePXrEoEGDOHTokELyli9fzvz58wkMDKRhw4aMHDmSkSNHoqWlJf/vkvTixQtOnjxJYGAgt27dokmTJmRkZNC3b1+2b9+ukMysrCwCAwOZOHEiPj4+pKenM3nyZHx8fPD19WXy5MnFmmdubs6ZM2cAaNy4MZGRkfKy0NBQTExMijXvTVq0aMHBgwcZP348f/31F506daJdu3b06dNHYZlZWVncuXMHgHr16nH//n152b179zA0NFRYdrkkCSph0KBBkq+vryRJkuTg4CBJkiQFBARI3bt3V2ju9evXpe7du0tLliyRMjIypObNmys0778OHz4sjRo1SmrcuLHUrVs3afPmzdKjR4/k5adOnZLs7OyKPXfevHlSy5YtpebNm0tz5syRwsLC8pVfuXJFsrW1LdbMgIAAyc7OTlqzZo303XffSe3atZPWrVsnrVy5UrK3t5d+++23Ys37r2bNmr12+5MnT6SAgADp+++/V1h2jx49pEaNGkkODg5SmzZtpNGjR0uSJEmBgYFSx44dpRUrVigsuzwSUz0qIu9X/7wnWO3t7RX69R8gLS2N+fPnExkZye3btxWel5ejoyNdu3alV69e2NjYvFIeFxfHzz//zPjx44s1d+jQobi7u9OxY8fXznPHx8cTERFBmzZtijX35MmT/Pjjj0RERPDixQu0tLSoW7eufM5fkbp3786BAwcUmvE26enpREZG8vfffwPQv39/fH19efToEWPHjlX4OZ1yRdmfPELBdO7cWbp27ZokSZJ81H379m2pU6dOJVaHffv2Sd7e3iWWJ0mS5O/v/9rte/bsKdF6/Cs+Pl4puf81derUcpuv7LaXBWLEryK2bdvGjh07GDFiBEuWLGHRokVs3LgRFxcXhg8fruzqFavU1FTi4+MBcHFx4eDBg+T9M01MTKRv374KPdl35coVvvrqK+Li4sjOzgYgMzOTp0+fEhERobDcgsp7MrS85Su77WWBuIBLRXh5eaGurs727dvJzs5m1apV9OrVi6FDhyq7asUuJSUFV1dXUlJSAGjfvr28TJIkZDIZH330kULrMH/+fExMTKhbty4xMTG0atWKHTt2MGHCBIXmFpSyx2vKzFd228sCMeIXXuuLL7545z5fffWVwvKfPn1Kamoqrq6ur8w7a2lp5VtiqghNmzYlJCSE+/fvs2DBArZt28alS5dYsGABu3fvVmh2QSh71CtG/KpNjPhVRHZ2Nlu2bGHPnj08fPgQMzMzPvvsM/r166eQPF1dXXx9ffn444/R1dVVSMbbVKlSBci5YExNreRXHRsYGKCjo4O5uTk3btwAcj4M7t27V+J1EYTiJjp+FfHNN99w6NAhhgwZgqmpKTExMWzZsoXk5GSFTPfMmjWLhIQEPvjgA2bOnFnsx38XV1dX9u/fT8eOHd94kdSxY8cUll+7dm127dqFh4cHenp6XL16FS0trWK9YEsQlEV0/CrCz8+PHTt25LuHipOTE8OGDVPYPP+MGTPo2rUrI0eOlI/AS8q/J6zHjBmjlM52/PjxjBw5EicnJ7y9vfHw8EBDQ0Nh37AEoSSJjl9FZGdnv3J3RlNTUxITExWWWbFiRQIDA9HU1FRYxpu4uroC4O7unm/7jRs30NfXp3r16grNr1GjBidPnkRDQ4PevXtjbW1NQkICrVu3VmhuQSn71Jw4uavaxC0bVET//v2ZO3eufKVLWloaK1asUOhl9ADa2trvnGOfNm2awvLDw8Px9PQE4Oeff8bFxYUOHToodJoHwM3NjfT0dHnbbWxsSqzTX7JkCVFRUW/dZ/ny5WUyX9ltLy/EiL+Us7a2RiaTyUc5fn5+VKxYkYSEBDIyMqhatWqx3zOmsAICAli6dKlCjr18+XLs7e2RJIlNmzaxePFiKleuzNdff02HDh0Ukgk5J3efPn2Kvr6+wjLe5MmTJ/Kbz73pdtQdO3Ysk/nKbnt5IZZzlnIFufe9o6NjCdTkzfLeUre4OTs7ExwczO3bt3F1deXcuXNUqFBBoZkAY8eO5fTp09ja2r6ydFSRy1j/lZKSwuHDh9m3bx+XLl2iTZs2JfZcAGXnK7vt5YHo+FXc8+fPS/wpUf+lyHXVrVq14siRI/z2228EBATg6+vL/fv36du3L0FBQQrJhLdfx1ASHX9eYWFhzJs3jytXrlC1alV69+7NsGHDSuxJWcrMV3bbyyrR8auI0nwLAUV2/PPnz+fMmTM8fPiQGTNm0KRJE0aPHk379u0Vem5B2eLj4zl48CB+fn5cvnwZZ2dn3N3dMTMzY/Xq1WRmZrJ169Yyma/stpcHouNXEX379sXExISKFSvmu4XAgAEDGDJkiFLrpsiOPysri71796Kjo4OLiwt37tzh+PHjeHp6KvRr/5tG/JqamlSuXJm2bdvSrFkzhWT7+PgQHByMhYUFPXv2pGfPnvmmm6KiohR6ryJl5iu77eWFOLmrIiIjI9m2bZv8FgKDBw+mWbNmLFiwQOkdvyKpq6vTq1cv+WsLCwsGDRqk8FxNTU327NlDp06dMDMzIzY2lj/++ANnZ2eeP3/Ojh07mDt3Lp988kmxZxsbG+Pr64utre1ry2vUqKHQxxAqM1/ZbS8vxIhfRbRp04agoCDS09Pp0KGDfH7byclJ/tQmZVHkidYbN26wfPlybt68SVZWVr4yRS7pHDJkCAMGDMh3M7jg4GC2b9/Opk2bOH/+PHPmzMHf319hdcgrKyuL69evK+x5v6U5X9ltL4vEiF9FKOsWAkuWLMHNzY369eu/cR9FrqueM2cO2traDBs2TP4M1pIQHh5O27Zt821r2bIl48aNA3Kej/vgwQOFZAcHBzNr1izi4uLyXaykrq5eIudzlJmv7LaXF6LjVxHKuoWAstdVR0ZGcvLkyRK/UZyxsTGHDh3CxcVFvs3f35+qVasCOXPNirqNxbJly+jUqROGhoZERkbi6urKunXrFP4ErtKQr+y2lxsl9MAXoYju378v/7l586Z09+5d6f79+1JYWJj0yy+/SPfu3VN4HZKTk6Xdu3dLAwcOlGxsbKTRo0dLx44dkzIzMxWe3blzZ+nJkycKz/mvwMBAqUmTJtJnn30mTZw4Uerbt69ka2srHT9+XLp69arUrFkzaefOnQrJtrGxkTIyMqQ7d+5In332mSRJuc8+LgnKzFd228sLMeIv5dq3b//G6Rzpn4eSXL16VaF10NXVxd3dHXd3d/m66lGjRpXIuuoBAwYwZswYvLy8XhlhN2/eXCGZAG3btsXf358DBw4QFxdHu3btWLlyJSYmJsTFxfHDDz9Qp04dhWRXrlwZNTU1atSowe3btwGoW7cucXFxCskrTfnKbnt5ITr+Uk7R96QpiNetq161apV8XfXo0aMVtq560aJFAK+cPC6JDzxzc3NGjhz5ynZjY2OMjY0Vtoy1fv36rF27lhEjRmBkZMSJEyeoUKEC2traxZ5V2vKV3fZyQ9lfOYTSbfjw4VKjRo2kbt26SZs2bZIePXqUrzwyMlJq2rSpkmqnXIpqd3R0tOTi4iLFxMRIf/zxh9SwYUPJ2tpa2rp1q0LySlO+stteXojlnMJbzZkzB3d39zeuq05KSiIuLo66desqrA5JSUkcOXKE2NhYvL29uXr1Kg4ODgrLKyhFjfgjIiJo1KiRfIrv8ePHJCUlUatWrWLPKm35ym57eSE6fqHQSnJddXR0NIMGDaJSpUrcu3ePPXv24OrqyvLly+natavC899GUR1/ixYtOHbsGHp6esV+7NKer+y2lxfifvzCWwUHB9O+fXsaNmxIgwYNaNCgAY0bNy6x5XWLFi1i1KhR7N+/Hw0NDWrVqsWqVatYv359ieQrg6mpKdeuXSuX+cpue3khTu4Kb6XsddVXrlxhy5YtAPKv/x07dizTN2irVKkSnp6emJubU7Vq1Xyrunbs2FGm85Xd9vJCdPzCW92+fZvdu3cTGxvLqVOn6Ny5M7Vr12bChAnyJ2MpUsWKFbl58yZWVlbybXfu3CnxZwCXpGbNminsBnClPV/ZbS8vRMcvvJWy11X369cPHx8fRowYQWZmJocOHWLjxo2l4kpORV1NfObMmddeu6GpqcmUKVP46KOP6Natm0KylZ2v7LaXF+pz586dq+xKCKVXSEgIt27dwt7enoMHD2JiYsKjR484duwY3t7eCs+3tbVFXV0dX19fEhISiIiIoEePHgwZMuSdzwIuinPnzhEbG/vWnxo1agAorP03btzg5MmTtG/fHnt7e/T19QkKCsLa2pqqVavy3XffoaamRtOmTctcvrLbXm4odzWpUNqVt3XV9evXf+uPtbW1wuvQp08fKTQ0NN+2v//+W+rXr58kSTm3MOjQoUOZzFd228sLMdUjvFVqair79+9HJpNhZmZGYGBgiayrXrt27Tv3GTNmTLHnRkZGFvsxCys6OhobG5t826ytreV1q1u3LvHx8WUyX9ltLy/Eck7hrYYOHUpKSor8tZGRUYlcTHPmzBnOnDnDiRMnWLt2LceOHePatWsEBQWxdu3aEnkCU2pqKnFxcfIpnrt375bILTRq167N999/n2/b1q1bsbS0BHKm30xMTMpkvrLbXl6IC7iEt3J3d2fWrFlKW2kxffp0bG1t891++vfff+ePP/5gw4YNCsv18/Njzpw5vHz5Mt/2ypUrExwcrLBcyHkWgI+PDzo6OlSvXp0HDx6QlZXFunXrkCQJT09Pvv76azp37lzm8pXd9vJCdPzCWw0ZMoQzZ84obV21nZ0d58+fz3ciNysrCwcHB4WO+j/++GP69euHnp4eZ8+eZdCgQSxfvpzWrVszdOhQheX+KzExkePHjxMXF4epqSnt27dHV1eX58+fk5mZKX8uQFnMV3bbywMxxy+8lbLXVVeuXJkLFy7kuwVzcHAw1apVU2juw4cP8fLy4sGDB+zatYtGjRqxePFiBg8eXCIdv4GBwWuf51uxYkWFZys7X9ltLw9Exy+8lbLXVfv4+DB06FA+/vhjTExMuHfvHkePHmXJkiUKywSoUqUKGRkZmJiYcPfuXSDndgJPnjxRaK4glARxcld4KxsbGyIjI7GxsaFbt240a9aM69evU6VKFapWrcrixYvZtm2bwvI9PDzYuHGj/Jmr2trafP/99wq/QZuNjQ3z5s0jNTUVS0tLdu7cye+//y5GnULZoMSlpIIKUIV11e3bty/2Yz58+FAaPny4FBcXJ507d06yt7eXGjVqJPn5+RV7liCUNDHVI7yVKqyrfvbsWbEfU1tbm2+//RaA6tWrExISQnp6Oo8fPy72LEEoaWKqR3grVVhX/aZnEr+Pjz76KN9rDQ0NdHR0cHNzK/YsQShpYjmn8FaqsK66uB6IEhMTg7e3N9nZ2cTGxmJqapqvPDU1lUqVKuHv7//eWYKgTKLjF96ptK+rLs4nYZ04cYKnT58yd+5c5s2bl69MS0uL5s2bK3wpqSAomuj4BZWniEcgnj17FkdHx2I9piCUFmKOXxBew8HBga1bt9KlSxdsbW3p0KEDa9euRYyThLJArOoRVJ4iOuOtW7fy008/MWLECMzMzLhz5w6bN29GQ0ODESNGFHueIJQkMdUjlGrnzp177XZNTU0qV65MzZo1ef78ebFfWPXxxx+zZs0a6tWrJ98WFRXFyJEj+fPPP4s1SxBKmhjxC6Xa9OnTiY2NRU1NjUqVKhEfH092djbq6upkZmZSq1YtNm3aVOwd/9OnT6lTp06+bXXq1CEhIaFYcwRBGcQcv1Cqde/eHTc3N86dO8dff/3F+fPn6dOnDyNGjCA0NJSPPvqIBQsWFHtuvXr12L17d75tu3fvpm7dusWeJQglTUz1CKVa27ZtOXLkCDo6OvJtL1++pHPnzpw8eZL09HRatWr1ximhojp//jze3t40bNiQGjVqcO/ePa5du8bmzZtxcHAo1ixBKGlixC+Uaunp6a/cEfPx48ekpaUBkJmZibq6erHnHjt2jH379uHs7Iyenh7t27dn//797N27t9izBKGkiTl+oVRzc3Nj6NChDBs2DGNi2NDBAAACOklEQVRjY2JjY/nuu+/o2bMnz54944svvqB169bFkvXw4UNOnz4NwM6dO6lfvz41a9akZs2aABw/fhx/f38WLlxYLHmCoCyi4xdKtUmTJqGvr8+3335LXFwcJiYmeHh4MHjwYC5fvoy5uTnjx48vlqxKlSqxc+dOnjx5Qnp6OqtXr85XrqWlxahRo4olSxCUSczxC8JrDBkyhO+++07Z1RAEhRAdv1CqZWdnc/ToUW7cuEFWVla+sjFjxiipVoKg2sRUj1CqzZs3Dz8/P6ytrdHQyP1zVcStmAWhvBAdv1CqHTt2DF9fXxo2bKjsqghCmSGWcwqlWmZmJvXr11d2NQShTBEdv1Cqde/eXZxkFYRiJk7uCqXaZ599RmhoKBUqVKBy5cr5yo4dO6akWgmCahMdv1Cq/f77728sE8+/FYSiER2/IAhCOSNW9Qilmqen5xuXbu7YsaOEayMIZYPo+IVSzdnZOd/r+Ph4Dh06RO/evZVUI0FQfWKqR1A5UVFRLFiwgB9//FHZVREElSSWcwoqx9LSkitXrii7GoKgssRUj1Cq/fcBK5mZmRw4cABLS0vlVEgQygDR8QulmqenZ77Xampq1KpVi9mzZyupRoKg+sQcv1AqxcbGAvC6P89/V/mYmpqWaJ0EoawQHb9QKllbW7/zDpxXr14todoIQtkiOn6hVLp///4796lRo0YJ1EQQyh7R8QuCIJQzYjmnIAhCOSM6fkEQhHJGdPyCIAjljOj4BUEQypn/AxHIEoo//P9bAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = 7\n",
    "cols = corrmat.nlargest(k, 'label')['label'].index\n",
    "cm = np.corrcoef(train_centered_df[cols].values.T)\n",
    "sns.set(font_scale=1.25)\n",
    "hm = sns.heatmap(cm, cbar=True, annot=True, square=True, fmt='.2f', annot_kws={'size': 10}, \n",
    "yticklabels=cols.values, xticklabels=cols.values)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/seaborn/axisgrid.py:2065: UserWarning: The `size` parameter has been renamed to `height`; pleaes update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "cols = ['label','gray_14','lung_density','total_gray','gray_6','gray_7','gray_5']\n",
    "sns.pairplot(train[cols], size = 2.5)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_train = train_centered_df[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>gray_6</th>\n",
       "      <th>gray_7</th>\n",
       "      <th>gray_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5216.000000</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "      <td>5.216000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.742906</td>\n",
       "      <td>-1.843974e-15</td>\n",
       "      <td>-5.339916e-16</td>\n",
       "      <td>1.259111e-15</td>\n",
       "      <td>-1.336354e-15</td>\n",
       "      <td>3.890250e-16</td>\n",
       "      <td>-1.244063e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.437073</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "      <td>1.000096e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-8.481079e+00</td>\n",
       "      <td>-5.042037e+00</td>\n",
       "      <td>-5.196343e+00</td>\n",
       "      <td>-5.078521e+00</td>\n",
       "      <td>-5.280877e+00</td>\n",
       "      <td>-5.223107e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-7.313986e-01</td>\n",
       "      <td>-7.394767e-01</td>\n",
       "      <td>-7.167310e-01</td>\n",
       "      <td>-6.954582e-01</td>\n",
       "      <td>-6.849231e-01</td>\n",
       "      <td>-6.974575e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.501788e-01</td>\n",
       "      <td>-1.570540e-01</td>\n",
       "      <td>3.391326e-01</td>\n",
       "      <td>2.950886e-01</td>\n",
       "      <td>2.959727e-01</td>\n",
       "      <td>3.153649e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.978698e-01</td>\n",
       "      <td>6.750585e-01</td>\n",
       "      <td>8.882908e-01</td>\n",
       "      <td>8.477542e-01</td>\n",
       "      <td>8.385507e-01</td>\n",
       "      <td>8.452803e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.345292e+01</td>\n",
       "      <td>3.945690e+00</td>\n",
       "      <td>1.239456e+00</td>\n",
       "      <td>1.927578e+00</td>\n",
       "      <td>3.170572e+00</td>\n",
       "      <td>1.776906e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             label       gray_14  lung_density    total_gray        gray_6  \\\n",
       "count  5216.000000  5.216000e+03  5.216000e+03  5.216000e+03  5.216000e+03   \n",
       "mean      0.742906 -1.843974e-15 -5.339916e-16  1.259111e-15 -1.336354e-15   \n",
       "std       0.437073  1.000096e+00  1.000096e+00  1.000096e+00  1.000096e+00   \n",
       "min       0.000000 -8.481079e+00 -5.042037e+00 -5.196343e+00 -5.078521e+00   \n",
       "25%       0.000000 -7.313986e-01 -7.394767e-01 -7.167310e-01 -6.954582e-01   \n",
       "50%       1.000000  1.501788e-01 -1.570540e-01  3.391326e-01  2.950886e-01   \n",
       "75%       1.000000  6.978698e-01  6.750585e-01  8.882908e-01  8.477542e-01   \n",
       "max       1.000000  1.345292e+01  3.945690e+00  1.239456e+00  1.927578e+00   \n",
       "\n",
       "             gray_7        gray_5  \n",
       "count  5.216000e+03  5.216000e+03  \n",
       "mean   3.890250e-16 -1.244063e-15  \n",
       "std    1.000096e+00  1.000096e+00  \n",
       "min   -5.280877e+00 -5.223107e+00  \n",
       "25%   -6.849231e-01 -6.974575e-01  \n",
       "50%    2.959727e-01  3.153649e-01  \n",
       "75%    8.385507e-01  8.452803e-01  \n",
       "max    3.170572e+00  1.776906e+00  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_train.to_csv('top6_features_train.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Do the same steps for test dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:10: DataConversionWarning: Data with input dtype int64, float64 were all converted to float64 by the scale function.\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    }
   ],
   "source": [
    "pne_test = pd.read_csv('pneumonia_test_small.csv')\n",
    "columns = pne_test.columns\n",
    "nor_test = pd.read_csv('normal_test_small.csv')\n",
    "pne_test['label'] = 1\n",
    "nor_test['label'] = 0\n",
    "test = pd.concat([pne_test, nor_test], ignore_index=True) \n",
    "test = test.dropna()\n",
    "test_df = test[columns]\n",
    "#center the variables\n",
    "test_centered = preprocessing.scale(test_df, with_mean='True', with_std='False')\n",
    "#convert back into a Pandas dataframe and add column names\n",
    "test_centered_df = pd.DataFrame(test_centered, columns=columns)\n",
    "test_centered_df['label'] = test['label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gray_0</th>\n",
       "      <th>gray_1</th>\n",
       "      <th>gray_2</th>\n",
       "      <th>gray_3</th>\n",
       "      <th>gray_4</th>\n",
       "      <th>gray_5</th>\n",
       "      <th>gray_6</th>\n",
       "      <th>gray_7</th>\n",
       "      <th>gray_8</th>\n",
       "      <th>gray_9</th>\n",
       "      <th>...</th>\n",
       "      <th>gray_12</th>\n",
       "      <th>gray_13</th>\n",
       "      <th>gray_14</th>\n",
       "      <th>gray_15</th>\n",
       "      <th>total_gray</th>\n",
       "      <th>lung_density</th>\n",
       "      <th>r_lungsize</th>\n",
       "      <th>l_lungsize</th>\n",
       "      <th>fraction</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>6.240000e+02</td>\n",
       "      <td>624.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-7.508239e-17</td>\n",
       "      <td>4.134869e-16</td>\n",
       "      <td>-7.377468e-16</td>\n",
       "      <td>-3.414292e-16</td>\n",
       "      <td>6.353536e-16</td>\n",
       "      <td>1.605197e-15</td>\n",
       "      <td>-6.823246e-16</td>\n",
       "      <td>7.294735e-18</td>\n",
       "      <td>1.071258e-15</td>\n",
       "      <td>-1.719244e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>1.581890e-15</td>\n",
       "      <td>-6.707597e-17</td>\n",
       "      <td>5.647192e-16</td>\n",
       "      <td>-7.112366e-17</td>\n",
       "      <td>9.191366e-16</td>\n",
       "      <td>2.028292e-17</td>\n",
       "      <td>2.292059e-16</td>\n",
       "      <td>1.329065e-16</td>\n",
       "      <td>-2.704389e-17</td>\n",
       "      <td>0.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>1.000802e+00</td>\n",
       "      <td>0.484511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.177206e+00</td>\n",
       "      <td>-6.867010e+00</td>\n",
       "      <td>-3.313255e+00</td>\n",
       "      <td>-4.568556e+00</td>\n",
       "      <td>-4.582806e+00</td>\n",
       "      <td>-4.512371e+00</td>\n",
       "      <td>-4.591670e+00</td>\n",
       "      <td>-4.574630e+00</td>\n",
       "      <td>-4.493416e+00</td>\n",
       "      <td>-4.628902e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.627459e+00</td>\n",
       "      <td>-4.143937e+00</td>\n",
       "      <td>-4.084506e+00</td>\n",
       "      <td>-3.847010e-01</td>\n",
       "      <td>-4.615015e+00</td>\n",
       "      <td>-2.121234e+00</td>\n",
       "      <td>-3.161082e+00</td>\n",
       "      <td>-2.682181e+00</td>\n",
       "      <td>-2.860383e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-8.470047e-01</td>\n",
       "      <td>-6.503184e-01</td>\n",
       "      <td>-5.799759e-01</td>\n",
       "      <td>-6.721745e-01</td>\n",
       "      <td>-6.260810e-01</td>\n",
       "      <td>-6.656800e-01</td>\n",
       "      <td>-6.625018e-01</td>\n",
       "      <td>-6.315779e-01</td>\n",
       "      <td>-6.728440e-01</td>\n",
       "      <td>-6.703401e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.006474e-01</td>\n",
       "      <td>-6.961202e-01</td>\n",
       "      <td>-7.170293e-01</td>\n",
       "      <td>-3.475007e-01</td>\n",
       "      <td>-6.587647e-01</td>\n",
       "      <td>-7.642557e-01</td>\n",
       "      <td>-6.373844e-01</td>\n",
       "      <td>-5.394498e-01</td>\n",
       "      <td>-5.485315e-01</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-4.159228e-01</td>\n",
       "      <td>1.419680e-01</td>\n",
       "      <td>1.503834e-01</td>\n",
       "      <td>3.218746e-01</td>\n",
       "      <td>3.322774e-01</td>\n",
       "      <td>3.438682e-01</td>\n",
       "      <td>3.749810e-01</td>\n",
       "      <td>3.902305e-01</td>\n",
       "      <td>3.582027e-01</td>\n",
       "      <td>3.380910e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.976015e-01</td>\n",
       "      <td>1.653555e-01</td>\n",
       "      <td>2.389593e-01</td>\n",
       "      <td>-2.358999e-01</td>\n",
       "      <td>3.564550e-01</td>\n",
       "      <td>-1.453712e-01</td>\n",
       "      <td>-5.697557e-02</td>\n",
       "      <td>4.648178e-02</td>\n",
       "      <td>1.602275e-01</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.692477e-01</td>\n",
       "      <td>5.415100e-01</td>\n",
       "      <td>5.389868e-01</td>\n",
       "      <td>8.131981e-01</td>\n",
       "      <td>8.306238e-01</td>\n",
       "      <td>8.371938e-01</td>\n",
       "      <td>8.372360e-01</td>\n",
       "      <td>8.415814e-01</td>\n",
       "      <td>8.120705e-01</td>\n",
       "      <td>8.162084e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>8.483845e-01</td>\n",
       "      <td>7.521161e-01</td>\n",
       "      <td>7.561888e-01</td>\n",
       "      <td>-4.989846e-02</td>\n",
       "      <td>8.679839e-01</td>\n",
       "      <td>6.662002e-01</td>\n",
       "      <td>6.139249e-01</td>\n",
       "      <td>6.832713e-01</td>\n",
       "      <td>5.917433e-01</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.594225e+00</td>\n",
       "      <td>5.513504e+00</td>\n",
       "      <td>8.793353e+00</td>\n",
       "      <td>1.750237e+00</td>\n",
       "      <td>1.397350e+00</td>\n",
       "      <td>1.207708e+00</td>\n",
       "      <td>1.262179e+00</td>\n",
       "      <td>1.246961e+00</td>\n",
       "      <td>1.321895e+00</td>\n",
       "      <td>1.283887e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.791914e+00</td>\n",
       "      <td>2.621518e+00</td>\n",
       "      <td>2.277502e+00</td>\n",
       "      <td>1.646703e+01</td>\n",
       "      <td>1.015994e+00</td>\n",
       "      <td>3.333795e+00</td>\n",
       "      <td>6.862818e+00</td>\n",
       "      <td>2.427159e+00</td>\n",
       "      <td>4.169076e+00</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             gray_0        gray_1        gray_2        gray_3        gray_4  \\\n",
       "count  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02   \n",
       "mean  -7.508239e-17  4.134869e-16 -7.377468e-16 -3.414292e-16  6.353536e-16   \n",
       "std    1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00   \n",
       "min   -1.177206e+00 -6.867010e+00 -3.313255e+00 -4.568556e+00 -4.582806e+00   \n",
       "25%   -8.470047e-01 -6.503184e-01 -5.799759e-01 -6.721745e-01 -6.260810e-01   \n",
       "50%   -4.159228e-01  1.419680e-01  1.503834e-01  3.218746e-01  3.322774e-01   \n",
       "75%    6.692477e-01  5.415100e-01  5.389868e-01  8.131981e-01  8.306238e-01   \n",
       "max    4.594225e+00  5.513504e+00  8.793353e+00  1.750237e+00  1.397350e+00   \n",
       "\n",
       "             gray_5        gray_6        gray_7        gray_8        gray_9  \\\n",
       "count  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02   \n",
       "mean   1.605197e-15 -6.823246e-16  7.294735e-18  1.071258e-15 -1.719244e-15   \n",
       "std    1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00   \n",
       "min   -4.512371e+00 -4.591670e+00 -4.574630e+00 -4.493416e+00 -4.628902e+00   \n",
       "25%   -6.656800e-01 -6.625018e-01 -6.315779e-01 -6.728440e-01 -6.703401e-01   \n",
       "50%    3.438682e-01  3.749810e-01  3.902305e-01  3.582027e-01  3.380910e-01   \n",
       "75%    8.371938e-01  8.372360e-01  8.415814e-01  8.120705e-01  8.162084e-01   \n",
       "max    1.207708e+00  1.262179e+00  1.246961e+00  1.321895e+00  1.283887e+00   \n",
       "\n",
       "          ...           gray_12       gray_13       gray_14       gray_15  \\\n",
       "count     ...      6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02   \n",
       "mean      ...      1.581890e-15 -6.707597e-17  5.647192e-16 -7.112366e-17   \n",
       "std       ...      1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00   \n",
       "min       ...     -4.627459e+00 -4.143937e+00 -4.084506e+00 -3.847010e-01   \n",
       "25%       ...     -7.006474e-01 -6.961202e-01 -7.170293e-01 -3.475007e-01   \n",
       "50%       ...      1.976015e-01  1.653555e-01  2.389593e-01 -2.358999e-01   \n",
       "75%       ...      8.483845e-01  7.521161e-01  7.561888e-01 -4.989846e-02   \n",
       "max       ...      1.791914e+00  2.621518e+00  2.277502e+00  1.646703e+01   \n",
       "\n",
       "         total_gray  lung_density    r_lungsize    l_lungsize      fraction  \\\n",
       "count  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02  6.240000e+02   \n",
       "mean   9.191366e-16  2.028292e-17  2.292059e-16  1.329065e-16 -2.704389e-17   \n",
       "std    1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00  1.000802e+00   \n",
       "min   -4.615015e+00 -2.121234e+00 -3.161082e+00 -2.682181e+00 -2.860383e+00   \n",
       "25%   -6.587647e-01 -7.642557e-01 -6.373844e-01 -5.394498e-01 -5.485315e-01   \n",
       "50%    3.564550e-01 -1.453712e-01 -5.697557e-02  4.648178e-02  1.602275e-01   \n",
       "75%    8.679839e-01  6.662002e-01  6.139249e-01  6.832713e-01  5.917433e-01   \n",
       "max    1.015994e+00  3.333795e+00  6.862818e+00  2.427159e+00  4.169076e+00   \n",
       "\n",
       "            label  \n",
       "count  624.000000  \n",
       "mean     0.625000  \n",
       "std      0.484511  \n",
       "min      0.000000  \n",
       "25%      0.000000  \n",
       "50%      1.000000  \n",
       "75%      1.000000  \n",
       "max      1.000000  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_centered_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_test = test_centered_df[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_test.to_csv('top6_features_test.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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