A python implementation of multinomial Naive Bayes classifier. In this sample, the classifier identifies the fortune cookie lines as a wise saying or a prediction.
Outputs the percentage of correctly tested objects to the "results.txt" file in /data.
Test data will be lower than the trained data, but this is to be expected. Trained data should produce a >95% success rate to be considered effective.