Unsupervised feature ranking approach based on probability density interval
Yaping Li · Jisuanji gongcheng yu sheji · 2007
High dimensional datasets often exist in pattern recognition and data analysis.In order to effectively analyze these datasets,reducing their dimensional members is a pivotal step.Based on probability density interval,a novel unsupervised feature ranking approach is proposed.Several cross-validation experimental results demonstrate the advantage of our approach here over others.