A number of feature selection mechanisms have been explored in text categorization, among which mutual information, information gain and chi-square are considered most effective. ...
Sanasam Ranbir Singh, Hema A. Murthy, Timothy A. G...
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...