Indira Gandhi National Tribal University, Amarkantak

Prof. Ram Dayal Munda Central Library

Online Public Access Catalogue

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Ensemble classification methods with applications in R / edited by Esteban Alfaro, Matías Gámez and Noelia García.

Contributor(s): Material type: TextTextPublisher: Hoboken, NJ : John Wiley & Sons, Inc., 2019Copyright date: ©2019Description: 1 online resource (xix, 200 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119421573
  • 1119421578
  • 9781119421559
  • 1119421551
Subject(s): Genre/Form: Additional physical formats: Print version:: Ensemble classification methods with applications in RDDC classification:
  • 006.3/1 23
LOC classification:
  • Q325.5 .E568 2019
Online resources:
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.
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Includes bibliographical references and index.

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.

Description based on online resource; title from digital title page (viewed on October 17, 2018).

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