Evaluating Learning Algorithms: A Classification Perspective

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The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have

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The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues. This book examines various aspects of the evaluation process with an emphasis on classification algorithms. The authors describe several techniques for classifier performance assessment, error estimation and resampling, obtaining statistical significance as well as selecting appropriate domains for evaluation. They also present a unified evaluation framework and highlight how different components of evaluation are both significantly interrelated and interdependent. The techniques presented in the book are illustrated using R and WEKA facilitating better practical insight as well as implementation. Aimed at researchers in the theory and applications of machine learning, this book offers a solid basis for conducting performance evaluations of algorithms in practical settings.

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Author

Nathalie Japkowicz, Mohak Shah

Binding

Paperback

EAN

9781107653115

EANList

9781107653115

ISBN

1107653118

IsEligibleForTradeIn

1

ItemDimensions

79, hundredths-inches, 906, hundredths-inches, 130, hundredths-pounds, 630, hundredths-inches

Label

Cambridge University Press

Languages

English, Unknown, English, Original Language, English, Published

Manufacturer

Cambridge University Press

NumberOfItems

1

NumberOfPages

424

PackageQuantity

1

ProductGroup

Book

PublicationDate

2014-06-05

Publisher

Cambridge University Press

ReleaseDate

2014-03-06

Studio

Cambridge University Press

TradeInValue

2251, USD, $22.51