Using Naive Bayes Classifier we were able to classify name into males and females with 78% accuracy.
Principle of Naive Bayes Classifier: A Naive Bayes classifier is a probabilistic machine learning model that’s used for classification task. The crux of the classifier is based on the Bayes theorem.
Bayes Theorem: P(A|B) = P(B|A)*P(A) / P(B)
Using Bayes theorem, we can find the probability of A happening, given that B has occurred. Here, B is the evidence and A is the hypothesis. The assumption made here is that the predictors/features are independent. That is presence of one particular feature does not affect the other. Hence it is called naive.