Probabilistic Learning

Abstract

This chapter is concerned with the probabilistic learning that is based on conditional probabilities of categories given an example. We mention the probability theory, which is called Bayes Theorem, in order to provide the background for understanding the chapter. We describe in detail some probabilistic classifiers such as Bayes Classifier and Naive Bayes as the popular and simple machine learning algorithms. We cover the Bayesian Learning as the more advanced learning methods than the two probabilistic learning algorithms. Among the probabilistic learning algorithms, the Naive Bayes is used as the most popular classifier to real classification tasks including text categorization. This chapter is concerned with the probabilistic learning that is based on conditional probabilities of categories given an example. We mention the probability theory, which is called Bayes Theorem, in order to provide the background for understanding the chapter. We describe in detail some probabilistic classifiers such as Bayes Classifier and Naive Bayes as the popular and simple machine learning algorithms. We cover the Bayesian Learning as the more advanced learning methods than the two probabilistic learning algorithms. Among the probabilistic learning algorithms, the Naive Bayes is used as the most popular classifier to real classification tasks including text categorization.