Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
Abstract. Feature selection researchers often encounter a peaking phenomenon: a feature subset can be found that is smaller but still enables building a more accurate classifier th...
Text categorisation relies heavily on feature selection. Both the possible reduction in dimensionality as well as improvements in classification performance are highly desirable. ...
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Abstract. In this paper we propose a supervised method for the segmentation of masses in mammographic images. The algorithm starts with a selected pixel inside the mass, which has ...