We present a novel feature screening algorithm by deriving relevance measures from the decision boundary of Support Vector Machines. It alleviates the "independence" assu...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
—We carried out a series of experiments on text classification using multi-word features. An automated method was proposed to extract the multi-words from text data set and two d...
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...