Ensemble methods : foundations and algorithms.

Mostrar otras versiones (2)

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After pr...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Zhou, Zhi-Hua (Computer scientist)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken : CRC Press, 2012.
Colección:Chapman & Hall/CRC Machine Learning & Pattern Recognition.
Temas:
Mathematical analysis.
Multiple comparisons (Statistics)
Set theory.
Analyse mathématique.
Corrélation multiple (Statistique)
Théorie des ensembles.
Mathematical analysis
Set theory
Acceso en línea:Texto completo
Descripción
Sumario:An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity a.
Descripción Física:1 online resource (234 pages)
ISBN:9781439830055
1439830053

Ejemplares similares