Add to ORKGData classification is one of the main techniques of data mining. Different mathematical programming approaches of the data classification were presented in recent years. A technique that uses polyhedral conic functions (PCF) is an effective method for data classification. We present a modified classification algorithm based on PCF functions. Results of numerical experiments on real-world and synthetic data sets demonstrate that the proposed approach is efficient for solving binary data classification problems
summary:A lower bound for the number of comparisons is obtained, required by a computational problem...
The polyhedral approach is one of the most powerful techniques available for solving hard combinator...
In this paper we propose a new algorithm for learning polyhedral classifiers which we call as Polyce...
WOS: 000438061200001In direct proportion to the heavy increase of online information data, the atten...
Incremental Conic Functions (ICF) algorithm is developed for solving classification problems based o...
In this paper, a piecewise linear classifier based on polyhedral conic separation is developed. This...
In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is devel...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existin...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existin...
© 2017 IEEE. We propose the novel data analysis algorithm which allows to identify exactly the posit...
In the context of learning theory many efforts have been devoted to developing classification algori...
Machine learning problems of supervised classification, unsupervised clustering and parsimonious app...
We study the problem of binary classification from the point of view of learning convex polyhedra in...
We consider polyhedral separation of sets as a possible tool in supervised classification. In partic...
International audienceWe propose a family of quasi-linear discriminants that outperform current larg...
summary:A lower bound for the number of comparisons is obtained, required by a computational problem...
The polyhedral approach is one of the most powerful techniques available for solving hard combinator...
In this paper we propose a new algorithm for learning polyhedral classifiers which we call as Polyce...
WOS: 000438061200001In direct proportion to the heavy increase of online information data, the atten...
Incremental Conic Functions (ICF) algorithm is developed for solving classification problems based o...
In this paper, a piecewise linear classifier based on polyhedral conic separation is developed. This...
In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is devel...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existin...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existin...
© 2017 IEEE. We propose the novel data analysis algorithm which allows to identify exactly the posit...
In the context of learning theory many efforts have been devoted to developing classification algori...
Machine learning problems of supervised classification, unsupervised clustering and parsimonious app...
We study the problem of binary classification from the point of view of learning convex polyhedra in...
We consider polyhedral separation of sets as a possible tool in supervised classification. In partic...
International audienceWe propose a family of quasi-linear discriminants that outperform current larg...
summary:A lower bound for the number of comparisons is obtained, required by a computational problem...
The polyhedral approach is one of the most powerful techniques available for solving hard combinator...
In this paper we propose a new algorithm for learning polyhedral classifiers which we call as Polyce...