Gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on classification algorithms.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Nathalie Japkowicz is Professor of Computer Science at American University. She is a former assistant professor at Dalhousie University and lecturer at Ohio State University. Japkowicz co-organized numerous workshops on classifier evaluation and the class imbalance problem at AAAI and ICML. She has published many articles in peer-reviewed journals and conference proceedings.
Mohak Shah is a Postdoctoral Fellow at the Centre for Intelligent Machines at McGill University. He is a former CIHR Postdoctoral Fellow at the CHUL Genomics research centre and Laval University in Quebec. He has been named the Arnold Smith Commonwealth Scholar in 2002 and a National Scholar in India in 1995. Shah has served on program committees of various conferences and symposiums in addition to reviewing for major journals and conferences in the field.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_440184701
Quantité disponible : 1 disponible(s)
Vendeur : COLLINS BOOKS, Seattle, WA, Etats-Unis
Hardcover. Etat : Very Good. 1st edition. 406pp, octavo, tight binding, clean throughout, glossy boards with mild wear, two thin scratches to back cover, sharp corners. N° de réf. du vendeur 163051
Quantité disponible : 1 disponible(s)
Vendeur : Gate City Books, GREENSBORO, NC, Etats-Unis
Etat : good. USED book in GOOD condition. Great binding, pages and cover show normal signs of wear from use. N° de réf. du vendeur GCM.LBX
Quantité disponible : 1 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Feb2215580247360
Quantité disponible : Plus de 20 disponibles
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9780521196000
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780521196000_new
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. 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. This book gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on classification algorithms. The authors describe several techniques designed to deal with performance measures and methods, error estimation or re-sampling techniques, statistical significance testing, data set selection and evaluation benchmark design. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521196000
Quantité disponible : 1 disponible(s)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 406 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __0521196000
Quantité disponible : 1 disponible(s)
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. 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. This book gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on classification algorithms. The authors describe several techniques designed to deal with performance measures and methods, error estimation or re-sampling techniques, statistical significance testing, data set selection and evaluation benchmark design. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9780521196000
Quantité disponible : 1 disponible(s)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 424. N° de réf. du vendeur 262099876
Quantité disponible : 4 disponible(s)