Actions for Machine learning with R : expert techniques for predictive modeling

Email RIS file
Bookmark
Report an Issue

Machine learning with R : expert techniques for predictive modeling / Brett Lantz

Author
Lantz, Brett
Published
Birmingham, UK : Packt, [2019]
Edition
Third edition.
Physical Description
1 online resource (xiii, 437 pages) : illustrations
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
Contents
Introducing machine learning -- Managing and understanding data -- Lazy learning -- classification using nearest neighbors -- Probabilistic learning -- classification using naive Bayes -- Divide and conquer -- classification using decision trees and rules -- Forecasting numeric data -- regression methods -- Black box methods -- neural networks and support vector machines -- Finding patterns -- market basket analysis using association rules -- Finding groups of data -- clustering with k-means -- Evaluation model performance -- Improving model performance -- Specialized machine learning topics.
Summary
A hands-on, readable guide to machine learning with R. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights and make new predictions. The 3rd edition features newer and better libraries, advice on ethical and bias issues, and an introduction to deep learning.
Subject(s)
Genre(s)
ISBN
9781523125241
1523125241
9781788291552 (electronic book)
1788291557 (electronic book)
9781788295864
1788295862
Note
Includes index.
Bibliography Note
Includes bibliographical references and index.
Terms of Use and Reproduction
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
View MARC record | catkey: 36196816