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

Format:

Book

Contributor:

Alfaro, Esteban, 1977- editor.

Gámez, Matías, 1966- editor.

García, Noelia, 1973- editor.

Language:

English

Subjects (All):

Machine learning--Statistical methods.

Machine learning.

R (Computer program language).

Physical Description:

xix, 200 pages ; 26 cm

Place of Publication:

Hoboken, NJ : John Wiley & Sons, Inc., 2019.

Contents:

Introduction

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.

Notes:

Includes bibliographical references and index.

Other Format:

Online version: Ensemble classification methods with applications in R.

ISBN:

9781119421092

1119421098

OCLC:

1044781995