Regression-test Model for High Dimensional Feature Selection

P. Bo and F. Jufu (PRC)


Feature Selection; Gene selection; Regression-Test model; Pattern Recognition; Bio-informatics;


Feature selection is a classical problem in pattern recognition. Feature selection when the number of features is much higher than the number of samples is a new issue that we seldom face before. But now more and more such problems emerge out. Gene selection, an important issue in medicine and biology [1], is such a problem. Many of traditional feature selection methods cannot perform well in that case. This paper proposes a Regression-Test model for high dimension feature selection. This method has a good performance when the dimension of feature space is very high. Experiment result in public data has demonstrated the validity of it.

Important Links:

Go Back