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To compare the effectiveness of the Naive Bayes model, Linear Trend, and a Weighted Average combination for predicting future values

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SirDre/sklearn_predictions

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Actual model predictions

To compare the effectiveness of the Naive Bayes model, Linear Trend, and a Weighted Average combination for predicting future values.

Dependencies


requires scikit-learn:

- Python (>= |PythonMinVersion|)
- NumPy (>= |NumPyMinVersion|)
- SciPy (>= |SciPyMinVersion|)
- joblib (>= |JoblibMinVersion|)
- threadpoolctl (>= |ThreadpoolctlMinVersion|)

User installation

Install pandas is using ::

pip install pandas
or
sudo apt-get install python3-pandas

Install matplotlib is using ::

pip install matplotlib
or
sudo apt-get install python3-matplotlib

Install statsmodels is using ::

pip install statsmodels
or
sudo apt-get install python3-statsmodels

Install scikit-learn is using ::

pip install -U scikit-learn
or
sudo apt-get install python3-sklearn

Testing


After installation, you can run the test data::

    python actual_model_predictions.py

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To compare the effectiveness of the Naive Bayes model, Linear Trend, and a Weighted Average combination for predicting future values

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