Gaussian Naive Bayes (GaussianNB) classifier not working with large number of features
It is not the number of features that is the problem with Gaussian Naive Bayes (GaussianNB). It is the decision boundary that GaussianNB is learning. Naive Bayes is constrained to the learn the marginal distribution of the data because &quot;naive&quot; assumption. Often times the conditional distribution is useful to make predictions. Given the performance of GaussianNB on that dataset, it might make sense to apply a different classifier that can learn a different decision boundary.