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48: fixing the issue by using contractions and stopwords #70

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48: fixing the issue by using contractions and stopwords #70

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5 changes: 4 additions & 1 deletion ML/Fake NEWS/Models/Jupyter Notebook/aossie-fakenews-tfidf-mnb.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -506,6 +506,8 @@
"import numpy as np\n",
"from sklearn import feature_extraction\n",
"from tqdm import tqdm\n",
"import contractions\n",
"from nltk.corpus import stopwords \n",
"\n",
"\n",
"_wnl = nltk.WordNetLemmatizer()\n",
Expand All @@ -522,13 +524,14 @@
"\n",
"def clean(s):\n",
" # Cleans a string: Lowercasing, trimming, removing non-alphanumeric\n",
" s = contractions.fix(s)\n",
"\n",
" return \" \".join(re.findall(r'\\w+', s, flags=re.UNICODE)).lower()\n",
"\n",
"\n",
"def remove_stopwords(l):\n",
" # Removes stopwords from a list of tokens\n",
" return [w for w in l if w not in feature_extraction.text.ENGLISH_STOP_WORDS]\n",
" return [w for w in l if w not in stopwords.words('english')] # Use stopwords.words('english')\n",
"\n",
"\n",
"def gen_or_load_feats(feat_fn, headlines, bodies, feature_file):\n",
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