I have two Naïve Bayes classifiers
nb_classifier = MultinomialNB(alpha=0.05, fit_prior=True) nb_classifier.fit(X_train, y_train)
nb_classifier = MultinomialNB(alpha=1, fit_prior=True) nb_classifier.fit(X_train, y_train)
where the only difference is the alpha value.
How do I choose the classifier that performs best?
I guess I should both classifiers with my test data set, but what should I look for when I claim one of them to be better than the other?
Should I use