Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions - Couverture souple

Seni, Giovanni; Elder, John

 
9781608452842: Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions
Couverture souple
ISBN 10 : 1608452840 ISBN 13 : 9781608452842
Editeur : Morgan and Claypool Publishers, 2010

Synopsis

This book is aimed at novice and advanced analytic researchers and practitioners -- especially in Engineering, Statistics, and Computer Science. Those with little exposure to ensembles will learn why and how to employ this breakthrough method, and advanced practitioners will gain insight into building even more powerful models. Throughout, snippets of code in R are provided to illustrate the algorithms described and to encourage the reader to try the techniques. The authors are industry experts in data mining and machine learning who are also adjunct professors and popular speakers. Although early pioneers in discovering and using ensembles, they here distill and clarify the recent groundbreaking work of leading academics (such as Jerome Friedman) to bring the benefits of ensembles to practitioners. The practical implementations of ensemble methods are enormous. Most current implementations of them are quite primitive and this book will definitely raise the state of the art. Giovanni Seni's thorough mastery of the cutting-edge research and John Elder's practical experience have combined to make an extremely readable and useful book. - from Foreword 1 by Jaffray Woodriff

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book is aimed at novice and advanced analytic researchers and practitioners -- especially in Engineering, Statistics, and Computer Science. Those with little exposure to ensembles will learn why and how to employ this breakthrough method, and advanced practitioners will gain insight into building even more powerful models. Throughout, snippets of code in R are provided to illustrate the algorithms described and to encourage the reader to try the techniques. The authors are industry experts in data mining and machine learning who are also adjunct professors and popular speakers. Although early pioneers in discovering and using ensembles, they here distill and clarify the recent groundbreaking work of leading academics (such as Jerome Friedman) to bring the benefits of ensembles to practitioners. The practical implementations of ensemble methods are enormous. Most current implementations of them are quite primitive and this book will definitely raise the state of the art. Giovanni Seni's thorough mastery of the cutting-edge research and John Elder's practical experience have combined to make an extremely readable and useful book. - from Foreword 1 by Jaffray Woodriff

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Morgan and Claypool Publishers
Date d'édition
2010
Langue
anglais
ISBN 10 
1608452840
ISBN 13 
9781608452842
Reliure
Broché
Nombre de pages
126
Coordonnées du fabricant
non disponible
Personne responsable
non disponible

Autres éditions populaires du même titre

9783031030277: Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions

Edition présentée

ISBN 10 :  3031030273 ISBN 13 :  9783031030277
Editeur : Springer, 2010
Couverture souple