Evaluating Learning Algorithms: a classification perspective (Record no. 34306)

000 -LEADER
fixed length control field 02859cam a2200205 i 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780521196000 (hbk.)
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number JAP/E
100 1# - MAIN ENTRY--AUTHOR NAME
Personal name Japkowicz, Nathalie.
245 10 - TITLE STATEMENT
Title Evaluating Learning Algorithms: a classification perspective
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Cambridge ;
-- New York :
Name of publisher Cambridge University Press,
Year of publication 2011.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xvi, 406 pages :
Other physical details illustrations ;
520 ## - SUMMARY, ETC.
Summary, etc "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"--
520 ## - SUMMARY, ETC.
Summary, etc "Technological advances, in recent decades, have made it possible to automate many tasks that previously required signi.cant amounts of manual time, performing regular or repetitive activities. Certainly, computing machines have proven to be a great asset in improving on human speed and e.ciency as well as in reducing errors in these essentially mechanical tasks. More impressively, however, the emergence of computing technologies has also enabled the automation of tasks that require signi.cant understanding of intrinsically human domains that can, in no way, be qualified as merely mechanical. While we, humans, have maintained an edge in performing some of these tasks, e.g. recognizing pictures or delineating boundaries in a given picture, we have been less successful at others, e.g., fraud or computer network attack detection, owing to the sheer volume of data involved, and to the presence of nonlinear patterns to be discerned and analyzed simultaneously within these data. Machine Learning and Data Mining, on the other hand, have heralded significant advances, both theoretical and applied, in this direction, thus getting us one step closer to realizing such goals"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer algorithms
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer Vision & Pattern Recognition
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer science
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Shah, Mohak.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type BK
952 ## - LOCATION AND ITEM INFORMATION (KOHA)
Withdrawn status
Lost status
Damaged status
Holdings
Collection code Home library Current library Shelving location Date acquired Cost, normal purchase price Full call number Accession Number Koha item type
Stack Kannur University Central Library Kannur University Central Library Stack 17/08/2015 95.00 006.31 JAP/E 31325 BK

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