Book Image

Learning Bayesian Models with R

By : Hari Manassery Koduvely
Book Image

Learning Bayesian Models with R

By: Hari Manassery Koduvely

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
Index

Summary


In this chapter, we discussed the concepts behind unsupervised and semi-supervised machine learning, and their Bayesian treatment. We learned two important Bayesian unsupervised models: the Bayesian mixture model and LDA. We discussed in detail the bgmm package for the Bayesian mixture model, and the topicmodels and lda packages for topic modeling. Since the subject of unsupervised learning is vast, we could only cover a few Bayesian methods in this chapter, just to give a flavor of the subject. We have not covered semi-supervised methods using both item labeling and feature labeling. Interested readers should refer to more specialized books in this subject. In the next chapter, we will learn another important class of models, namely neural networks.