Course Content

  • Naive_Bayes_Classifier

Course Content

FAQs

The Benefits of Using a Naive Bayes Classifier:

  • It is capable of dealing with both continuous and discrete data. It can handle a large number of predictors and data points. It is quick and can be used to make predictions in real time. It is unaffected by non-essential characteristics.

The generative model Naive Bayes is. (Gaussian) Each class in Naive Bayes is assumed to have a Gaussian distribution. The distinction between QDA and (Gaussian) Naive Bayes is that Naive Bayes assumes feature independence, resulting in diagonal covariance matrices.

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