The Naive Bayes Model, Maximum-Likelihood Estimation, and the EM Algorithm
نویسنده
چکیده
This section describes a model for binary classification, Naive Bayes. Naive Bayes is a simple but important probabilistic model. It will be used as a running example in this note. In particular, we will first consider maximum-likelihood estimation in the case where the data is “fully observed”; we will then consider the expectation maximization (EM) algorithm for the case where the data is “partially observed”, in the sense that the labels for examples are missing.
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