In this chapter, we discussed the various merits of using Bayesian inference for the classification task. We reviewed some of the common performance metrics used for the classification task. We also learned two basic and popular methods for classification, Naïve Bayes and logistic regression, both implemented using the Bayesian approach. Having learned some important Bayesian-supervised machine learning techniques, in the next chapter, we will discuss some unsupervised Bayesian models.
Learning Bayesian Models with R
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Learning Bayesian Models with R
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Overview of this book
Table of Contents (16 chapters)
Learning Bayesian Models with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Introducing the Probability Theory
The R Environment
Introducing Bayesian Inference
Machine Learning Using Bayesian Inference
Bayesian Regression Models
Bayesian Classification Models
Bayesian Models for Unsupervised Learning
Bayesian Neural Networks
Bayesian Modeling at Big Data Scale
Index
Customer Reviews