Skip to content

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

License

Notifications You must be signed in to change notification settings

SirDre/actual_model_predictions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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 scikit-learn is using ::

pip install -U scikit-learn

Testing


After installation, you can run the test data::

    python actual_model_predictions.py

About

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

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages