Add to ORKGAbstract: In this paper a generalization of Fisher’s linear discriminant is pro-posed. With this new procedure it is possible to estimate linear discriminant functions which are not affected by outlying observations. The proposed method and the classical method are compared by applying both to real and simulated data sets. The generalized approach has shown advantages over the classical one
In this paper, a modified Fisher linear discriminant analysis (FLDA) is proposed and aims to not onl...
AbstractA general integral expression is obtained for evaluating the performance of Fisher's linear ...
Fisher linear discriminant analysis (FLDA) $nds a set of optimal discriminating vectors by maximizin...
In the early seventies it was observed that discriminatory values obtained by the leaving-one-out me...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
In the article the application of kernel functions – the so-called »kernel trick« – in the context o...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
In this paper, we present an iterative approach to Fisher discriminant analysis called Kullback-Leib...
A non-linear classification technique based on Fisher's discriminant is proposed. Main ingredie...
A non-linear classification technique based on Fisher's discriminant is proposed. The main ingredien...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
Fisher's linear discriminant analysis is one of the most commonly used and studied classification me...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
A novel approach to semi-supervised learning for classical Fisher linear discriminant analysis is pr...
In this paper, a modified Fisher linear discriminant analysis (FLDA) is proposed and aims to not onl...
AbstractA general integral expression is obtained for evaluating the performance of Fisher's linear ...
Fisher linear discriminant analysis (FLDA) $nds a set of optimal discriminating vectors by maximizin...
In the early seventies it was observed that discriminatory values obtained by the leaving-one-out me...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;不具代表性[[note]]http://gateway.isiknowledge.com/gateway/G...
In the article the application of kernel functions – the so-called »kernel trick« – in the context o...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
In this paper, we present an iterative approach to Fisher discriminant analysis called Kullback-Leib...
A non-linear classification technique based on Fisher's discriminant is proposed. Main ingredie...
A non-linear classification technique based on Fisher's discriminant is proposed. The main ingredien...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
Fisher's linear discriminant analysis is one of the most commonly used and studied classification me...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
A novel approach to semi-supervised learning for classical Fisher linear discriminant analysis is pr...
In this paper, a modified Fisher linear discriminant analysis (FLDA) is proposed and aims to not onl...
AbstractA general integral expression is obtained for evaluating the performance of Fisher's linear ...
Fisher linear discriminant analysis (FLDA) $nds a set of optimal discriminating vectors by maximizin...