PacktLib: Machine Learning with R

Machine Learning with R

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

Introducing Machine Learning

The origins of machine learning

Uses and abuses of machine learning

How do machines learn?

Steps to apply machine learning to your data

Choosing a machine learning algorithm

Using R for machine learning

Summary

Managing and Understanding Data

R data structures

Vectors

Factors

Managing data with R

Exploring and understanding data

Summary

Lazy Learning – Classification Using Nearest Neighbors

Understanding classification using nearest neighbors

Diagnosing breast cancer with the kNN algorithm

Summary

Probabilistic Learning – Classification Using Naive Bayes

Understanding naive Bayes

Example – filtering mobile phone spam with the naive Bayes algorithm

Summary

Divide and Conquer – Classification Using Decision Trees and Rules

Understanding decision trees

Example – identifying risky bank loans using C5.0 decision trees

Understanding classification rules

Example – identifying poisonous mushrooms with rule learners

Summary

Forecasting Numeric Data – Regression Methods

Understanding regression

Example – predicting medical expenses using linear regression

Understanding regression trees and model trees

Example – estimating the quality of wines with regression trees and model trees

Summary

Black Box Methods – Neural Networks and Support Vector Machines

Understanding neural networks

Modeling the strength of concrete with ANNs

Understanding Support Vector Machines

Performing OCR with SVMs

Summary

Finding Patterns – Market Basket Analysis Using Association Rules

Understanding association rules

Example – identifying frequently purchased groceries with association rules

Summary

Finding Groups of Data – Clustering with k-means

Understanding clustering

Summary

Evaluating Model Performance

Measuring performance for classification

Estimating future performance

Summary

Improving Model Performance

Tuning stock models for better performance

Improving model performance with meta-learning

Summary

Specialized Machine Learning Topics

Working with specialized data

Improving the performance of R

Summary

Index