The minimum-distance classifier summarizes each class with a prototype and then uses a nearest neighbor approach for classification. Three drawbacks of the original minimum-distan...
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
In this paper, we propose a generic description of the concept lattice as classifier in an iterative recognition process. We also present the development of a new structural signat...
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
Jierui Xie, Boleslaw K. Szymanski, Mohammed J. Zak...