Téléchargez le livre : Recent Advances in Ensembles for Feature Selection

Recent Advances in Ensembles for Feature Selection



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Springer


Paru le : 2018-04-30



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Description

This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance.
With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative.
The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges thatresearchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining. 
Pages
205 pages
Collection
n.c
Parution
2018-04-30
Marque
Springer
EAN papier
9783319900797
EAN PDF
9783319900803
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
4884 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
96,29 €
EAN EPUB
9783319900803
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
6871 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
96,29 €

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