In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some fe...
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...