- R Machine Learning By Example
- Table of Contents
- R Machine Learning By Example
- Credits
- About the Authors
- About the Reviewer
- www.PacktPub.com
- Preface
- 1. Getting Started with R and Machine Learning
- 2. Let's Help Machines Learn
- 3. Predicting Customer Shopping Trends with Market Basket Analysis
- 4. Building a Product Recommendation System
- 5. Credit Risk Detection and Prediction – Descriptive Analytics
- 6. Credit Risk Detection and Prediction – Predictive Analytics
- Predictive analytics
- How to predict credit risk
- Important concepts in predictive modeling
- Getting the data
- Data preprocessing
- Feature selection
- Modeling using logistic regression
- Modeling using support vector machines
- Modeling using decision trees
- Modeling using random forests
- Modeling using neural networks
- Model comparison and selection
- Summary
- 7. Social Media Analysis – Analyzing Twitter Data
- 8. Sentiment Analysis of Twitter Data
- Index
This software applies to all the chapters of the book:
- Windows / Mac OS X / Linux
- R 3.2.0 (or higher)
- RStudio Desktop 0.99 (or higher)
For hardware, there are no specific requirements, since R can run on any PC that has Mac, Linux, or Windows, but a physical memory of minimum 4 GB is preferred to run some of the iterative algorithms smoothly.
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.