Introduction to Naive Bayes

The Naive Baye’s Classifier basically uses the Baye’s Theorem. According to the ‘statistics and probability’ and ‘probability theory’, the baye’s theorem is used to describe the probability for an event to occur based on the conditions related to the event that occurs. It is just an assumption which comes into picture based on the “independent character” among the predictors.
The classifier assumes; In a given class of several factors, the presence of a particular factor is always unrelated to any other factor present in the same class. The Naive Baye’s classifier is classified under the probabilistic classifier making assumptions which are independent of features and is closely related to the machine learning.