sethrcooper/TeamFineWine

Machine Learning Group Project About Classifying the Quality of Wine

Team Fine Wine

pip install -r requirements.txt

Naive Bayes

Training

1. Navigate to naive_bayes_test.ipynb
2. Run all cells

Testing

1. Navigate to WineClassifier.py
2. Execute WineClassifier.py
3. View results in console

CNN

Utilize Python 3.10.6

Training

1. Navigate to cnn/cnn.ipynb
2. Run all cells

Testing

1. Navigate to WineClassifier.py
2. Execute WineClassifier.py
3. View results in console

Multiclass Logistic Regression

Training

1. Navigate to WineClassifier.py
2. Ensure line 63 containing the function multi_logistic_regression is uncommented
3. Ensure line 65 containing the function predictPreset is commented out
4. Execute WineClassifier.py
5. View results in console

Testing

1. Navigate to WineClassifier.py
2. Ensure line 63 containing the function multi_logistic_regression is commented out
3. Ensure line 65 containing the function predictPreset is uncommented
4. Execute WineClassifier.py
5. View results in console

The function multi_logistic_regression trains a new weight vector for each random training-testing split each time WineClassifier.py is run and tests it on the testing subset

The function predictPreset makes predictions given X_test using a static weight vector pulled from a single run that averaged high results.