Simultaneous classification and feature clustering using discriminant vector quantization with applications to microarray data analysis.

Abstract excerpt

In many applications of supervised learning, automatic feature clustering is often desirable for a better understanding of the interaction among the various features as well as the interplay between the features and the class labels. In addition, for high dimensional data sets, feature clustering has the potential for improvement in classification accuracy and reduction in computational complexity. In this paper,...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Algorithms
• Share to Artificial Intelligence