Ensemble classification methods with applications in R

Ensemble classification methods with applications in R

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques. This...

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Detalles Bibliográficos
Otros Autores: Alfaro, Esteban, 1977- editor (editor), Gámez, Matías, editor, García, Noelia, editor
Formato: Libro electrónico
Publicado: Hoboken, N.J.: Wiley 2019.
Hoboken, N.J. : 2019.
Edición:1st edition
Materias:
Machine learning > Statistical methods
R (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630473906719
Tabla de Contenidos:
  • 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 GAM.

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