In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
This paper presents a data-driven approach for feature selection to address the common problem of dealing with high-dimensional data. This approach is able to handle the real-valu...
This paper presents an empirical study for improving the performance of text chunking. We focus on two issues: the problem of selecting feature spaces, and the problem of alleviat...
We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulati...
Jun Sun, Wenbo Zhao, Jiangwei Xue, Zhiyong Shen, Y...