http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
expert techniques for predictive modeling
1 online resource (xiii, 437 pages) : illustrations
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.
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.
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Includes bibliographical references and index.