An attribute-oriented rough set method for knowledgediscovery in databases is described. Themethodis based on information generalization, whichexaminesthe data at various levels o...
Ning Shan, Wojciech Ziarko, Howard J. Hamilton, Ni...
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
The problem of identifying mislabeled training examples has been examined in several studies, with a variety of approaches developed for editing the training data to obtain better...
Abstract. We present a novel approach for classification using a discretised function representation which is independent of the data locations. We construct the classifier as a su...
In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class label. Such cases arise...