Discriminant Analysis and Statistical Pattern Recognition

Geoffrey J. McLachlan - Collection Wiley Series in Probability and Statistics

530 pages, parution le 17/11/2004

Ajouter à une liste

Indisponible

Résumé

Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject area, concentrating on the most recent advances in the field. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are: regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule and extensions of discriminant analysis motivated by problems in statistical image analysis. Includes over 1,200 references in the bibliography.

Sommaire

Likelihood-Based Approaches to Discrimination
Discrimination via Normal Models
Distributional Results for Discrimination via Normal Models
Some Practical Aspects and Variants of Normal Theory-Based Discriminant Rules
Data Analytic Considerations with Normal Theory-Based Discriminant Analysis
Parametric Discrimination via Nonnormal Models
Logistic Discrimination
Nonparametric Discrimination
Estimation of Error Rates
Assessing the Reliability of the Estimated Posterior Probabilites of Group Membership
Selection of Feature Variables in Discriminant Analysis
Statistical Image Analysis

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Geoffrey J. McLachlan
Collection	Wiley Series in Probability and Statistics
Parution	17/11/2004
Nb. de pages	530
Format	15 x 23
Couverture	Broché
Poids	750g
Intérieur	Noir et Blanc
EAN13	9780471691150
ISBN13	978-0-471-69115-0