In this paper we discuss problems of constructing classifiers from imbalanced data. We describe a new approach to selective preprocessing of imbalanced data which combines local ov...
In this paper, we propose an approach based on Formal Concept Analysis in order to organize the services registry at runtime and to allow the "best" service selection am...
Abstract: We are developing a new mashup framework for creating flexible applications in which users can selectively browse through mashup items. The framework provides GUI compone...
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
This paper presents an extensive survey of model selection techniques for computer vision applications. A large number of existing model selection criteria...