Data Science Study Notes: What's the intuitive difference between Bayesian Classifier and Naive Bayesian Classifier?

• Most people understand the logic behind Bayesian Classifier, it's one of the must-learn Bayes theorem in stats, based on conditional probability. 

• Naive Bayesian Classifier is a simplified version of Bayesian Classifier, with the big assumption that all features x1, x2, ..., xk are all independent of each other, which is hardly to be true to get a set of predictors which are entirely independent in reality, especially if you didn't understand each feature very well, or didn't do the feature selection first.