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Title Ensemble classification methods with applications in R / edited by Esteban Alfaro, Matías Gámez and Noelia García. [O'Reilly electronic resource]

Publication Info. Hoboken, NJ : John Wiley & Sons, Inc., 2019.
©2019
To Access:
Available on O'Reilly for Public Libraries
Bookmark link: https://library.naperville-lib.org:444/record=b3179577~S1
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Description 1 online resource (xix, 200 pages)
Bibliography Includes bibliographical references and index.
Contents Limitation of the individual classifiers -- Ensemble classifiers methods -- Classification with individual and ensemble trees in R -- Bankrupcty prediction through ensemble trees -- Experiments with adabag in biology classification tasks -- Generalization bounds for ranking algorithms -- Classification and regression trees for analysing irrigation decisions -- Boosted rule learner and its properties -- Credit scoring with individuals and ensemble trees -- An overview of multiple classifier systems based on Generalized Additive Models.
Subject Machine learning -- Statistical methods.
R (Computer program language)
Apprentissage automatique -- Méthodes statistiques.
R (Langage de programmation)
Machine learning -- Statistical methods
R (Computer program language)
Added Author Alfaro, Esteban, 1977- editor.
Gámez, Matías, 1966- editor.
García, Noelia, 1973- editor.
Other Form: Print version: Ensemble classification methods with applications in R. Hoboken, NJ : John Wiley & Sons, 2018 9781119421092 (DLC) 2018022257
ISBN 9781119421573 (electronic book)
1119421578 (electronic book)
9781119421559 (electronic book)
1119421551 (electronic book)
(hardcover)
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