Evaluating Learning Algorithms: A Classification Perspective Mohak Shah » holypet.ru

This is truly a book to be savoured by machine learning professionals, and required reading for Ph.D students." Peter A. Flach, University of Bristol "This book has the merit of organizing most of the material about the evaluation of learning algorithms into a homogeneous description, covering both theoretical aspects and pragmatic issues. It focuses especially on algorithms for classification problems, but many of the discussions on specific arguments are broad enough to cover a wide range of learning problems. The book starts by illustrating a typical case study where a number of learning algorithms need to be evaluated on some datasets.

Jan 17, 2011 · 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. Evaluating Learning Algorithms: A Classification Perspective / Nathalie Japkowicz, Mohak Shah. p. cm. Includes bibliographical references. ISBN 978-0-521-19600-0 1. Machine learning. 2. Computer algorithms – Evaluation. I. Shah, Mohak. II. Title. Q325.5.J37 2011 006.3 1–dc22 2010048733 ISBN 978-0-521-19600-0 Hardback. Evaluating Learning Algorithms: A Classification Perspective / Nathalie Japkowicz, Mohak Shah. p. cm. Includes bibliographical references. ISBN 978-0-521-19600-0 1. A simple and intuitive mesure for multicriteria evaluation of classification algorithms. In Proceedings of the ECML 2000 Workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination, pp. 87–96. Springer, Berlin, 2000.

Evaluating Learning Algorithms A Classification Perspective NATHALIE JAPKOWICZ University of Ottawa MOHAK SHAH McGill University m. CAMBRIDGE UNIVERSITY PRESS. Contents Preface page xi. 8.4 Insights from Statistical Learning Theory 323 8.5 Other Developments 329 8.6 Summary 330 Appendix: Proof of Theorems 8.1 and 8.2 330. Mohak Shah is the author of Evaluating Learning Algorithms 4.00 avg rating, 7 ratings, 1 review, published 2011. Publisher description for Evaluating Learning Algorithms: A Classification Perspective / Nathalie Japkowicz, Mohak Shah. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues.

As a machine learning and AI scientist, Mohak has developed novel technologies with high impact business applications. He is the author of "Evaluating Learning Algorithms: A Classification Perspective" Cambridge, and has published more than 45 research articles, in top conferences and journals in the analytics space, and patented technologies. 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. descargar Evaluating learning algorithms. a classification perspective libro online completo pdf!

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