Add to ORKGThe empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule
The performance of four discriminant analysis procedures for the classification of observations from...
Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. Thi...
The incorporation of additional information into discriminant rules is receiving in- creasing attent...
This study provides a comprehensive review of the literature pertaining to the problem of classifica...
The problem of discriminating between two n-variate normal populations with known but unequal means ...
A new linear discrimination rule, designed for two-group problems with many correlated variables, is...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
This paper presents a fisher’s criterion, Welch’s criterion, and Bayes criterion for performing a di...
AbstractIn this paper some ideas on experimental designs are used in discriminant analysis. By consi...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
The following thesis studies both parametric and non parametric approaches to classification. Among ...
Building on probabilistic models for interval-valued variables, parametric classification rules, bas...
This dissertation considers the estimation of the chance of misclassification when a new observation...
The performance of four discriminant analysis procedures for the classification of observations from...
Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. Thi...
The incorporation of additional information into discriminant rules is receiving in- creasing attent...
This study provides a comprehensive review of the literature pertaining to the problem of classifica...
The problem of discriminating between two n-variate normal populations with known but unequal means ...
A new linear discrimination rule, designed for two-group problems with many correlated variables, is...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
Discriminant analysis is a statistical discriminant and grouping technique, which uses the sample da...
This paper presents a fisher’s criterion, Welch’s criterion, and Bayes criterion for performing a di...
AbstractIn this paper some ideas on experimental designs are used in discriminant analysis. By consi...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
The following thesis studies both parametric and non parametric approaches to classification. Among ...
Building on probabilistic models for interval-valued variables, parametric classification rules, bas...
This dissertation considers the estimation of the chance of misclassification when a new observation...
The performance of four discriminant analysis procedures for the classification of observations from...
Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. Thi...
The incorporation of additional information into discriminant rules is receiving in- creasing attent...