In this paper we introduce a non-parametric linear programming formulation for the general multigroup classification problem. Previous research using linear programming formulations has either been limited to the two-group case, or required complicated constraints and many zero-one variables. We develop general properties of our multigroup formulation and illustrate its use with several small example problems and previously published real data sets. A comparative analysis on the real data sets shows that our formulation may offer an interesting robust alternative to parametric statistical formulations for the multigroup discriminant problem
Managers have been grappling with the problem of extracting patterns out of the vast database genera...
A single linear program is proposed for discriminating between the elements of k disjoint point sets...
Mathematical programming (MP) can be used for developing classification models for the two–group cl...
A review is given on existing work and result of the performance of some discriminant analysis proce...
Discriminant Analysis (DA) is widely applied in many fields. Some recent researches raise the fact t...
In the last twelve years there has been considerable research interest in mathematical programming a...
This paper introduces a nonparametric formulation-based mathematical programming (MP) for solving t...
Various parametric and nonparametric approaches to multiple discriminant analysis attempt to discrim...
Various parametric and nonparametric approaches to multiple discriminant analysis attempt to discrim...
Abstract — Among various statistical and data mining discriminant analysis proposed so far for group...
Classification is concerned with the development of rules for the allocation of observations to grou...
Fisher--Rao Linear Discriminant Analysis (LDA), a valuable tool for multigroup classification and da...
This paper introduces a nonparametric formulation based on mathematical programming (MP) for solving...
Among the various discriminant analysis (DA) methods, researchers have investigated several directio...
Multivariate Analysis (MVA) is based on the Statistical principle of Multivariate Statistics which i...
Managers have been grappling with the problem of extracting patterns out of the vast database genera...
A single linear program is proposed for discriminating between the elements of k disjoint point sets...
Mathematical programming (MP) can be used for developing classification models for the two–group cl...
A review is given on existing work and result of the performance of some discriminant analysis proce...
Discriminant Analysis (DA) is widely applied in many fields. Some recent researches raise the fact t...
In the last twelve years there has been considerable research interest in mathematical programming a...
This paper introduces a nonparametric formulation-based mathematical programming (MP) for solving t...
Various parametric and nonparametric approaches to multiple discriminant analysis attempt to discrim...
Various parametric and nonparametric approaches to multiple discriminant analysis attempt to discrim...
Abstract — Among various statistical and data mining discriminant analysis proposed so far for group...
Classification is concerned with the development of rules for the allocation of observations to grou...
Fisher--Rao Linear Discriminant Analysis (LDA), a valuable tool for multigroup classification and da...
This paper introduces a nonparametric formulation based on mathematical programming (MP) for solving...
Among the various discriminant analysis (DA) methods, researchers have investigated several directio...
Multivariate Analysis (MVA) is based on the Statistical principle of Multivariate Statistics which i...
Managers have been grappling with the problem of extracting patterns out of the vast database genera...
A single linear program is proposed for discriminating between the elements of k disjoint point sets...
Mathematical programming (MP) can be used for developing classification models for the two–group cl...