In text categorization, feature selection (FS) is a strategy that aims at making text classifiers more efficient and accurate. However, when dealing with a new task, it is still d...
Although regarded as one of the most successful algorithm to identify predictive features, Relief is quite vulnerable to outliers and noisy features. The recently proposed I-Relief...
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...
A new efficient unsupervised feature selection method is proposed to handle transactional data. The proposed feature selection method introduces a new Data Distribution Factor (DDF...
We present an efficient feature selection algorithm for computer aided detection (CAD) computed tomographic (CT) colonography. The algorithm 1) determines an appropriate piecewise...
Jiang Li, Jianhua Yao, Ronald M. Summers, Nicholas...