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Mastering Predictive Analytics with R

You're reading from Mastering Predictive Analytics with R Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts

Product type Paperback

Published in Jun 2015

Publisher

ISBN-13 9781783982806

Length 414 pages

Edition 1st Edition

Languages

R

Tools

RStudio

Concepts

Predictive Analytics

Table of Contents (13) Chapters

Preface

1. Gearing Up for Predictive Modeling

2. Linear Regression FREE CHAPTER

3. Logistic Regression

4. Neural Networks

5. Support Vector Machines

6. Tree-based Methods

7. Ensemble Methods

8. Probabilistic Graphical Models

9. Time Series Analysis

10. Topic Modeling

11. Recommendation Systems

Index

Chapter 2. Linear Regression

We learned from the previous chapter that regression problems involve predicting a numerical output. The simplest but most common type of regression is linear regression. In this chapter, we'll explore why linear regression is so commonly used, its limitations, and extensions.

You have been reading a chapter from

Mastering Predictive Analytics with R

Published in: Jun 2015

Publisher:

ISBN-13: 9781783982806

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