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- Naive Bayes classifier assumes that the features are independent of each other.
- Naive Bayes classifier can be trained faster as compared to other classification algorithms.
- Naive Bayes classifier model can predict faster as compared to other classification algorithms.
- Naive Bayes classifier model can be modified with new training data without having to re build the model.
- Naive Bayes classifier model does not involve optimization of a cost function.
- Naive Bayes classifier training does not involve epoch.
- Naive Bayes classifier model does not involve solving a matrix equation.
- When assumptions of independence of features holds , Naive Bayes classifier model performs better than other classifiers.
- When assumptions of independence of features holds ,Naive Bayes classifier model needs less training data.
- Naive Bayes classifier model performs well in case of categorical input variables compared to numerical input variable.
