Understanding the Bayesian classification

We will now explore the Bayesian techniques that are used to classify data. A Bayes classifier is essentially a probabilistic classifier that is built using the Bayes' theorem of conditional probability. A model based on the Bayes classification assumes that the sample data has strongly independent features. By independent, we mean that every feature of the model can vary independent of the other features in the model. In other words, the features of the model are mutually exclusive. Thus, a Bayes classifier assumes that the presence or absence of a particular feature is completely independent of the presence or absence of the other features of the classification model.

The term is used to represent the ...

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