@inproceedings{4d19dc07527e46bbb0b7cbced1d36e02,
title = "Gene selection through sensitivity analysis of support vector machines",
abstract = "We present a novel approach to gene selection for microarry data through the sensitivity analysis of support vector machines (SVMs). A new measurement (sensitivity) is defined to quantify the saliencies of individual features (genes) by analyzing the discriminative function in SVMs. Our feature selection strategy is first to select the features with higher sensitivities but meanwhile keep the remaining ones, and then refine the selected subset by tentatively substituting some part with fragments of the previously rejected features. The accuracy of our method is validated experimentally on the benchmark microarray datasets.",
author = "Defeng Wang and Yeung, \{Daniel S.\} and Tsang, \{Eric C.C.\} and Lin Shi",
year = "2005",
doi = "10.1007/11560500\_11",
language = "英语",
isbn = "3540291040",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "117--127",
booktitle = "Computational Life Sciences - First International Symposium, CompLife 2005, Proceedings",
address = "德国",
note = "1st International Symposium on Computational Life Sciences, CompLife 2005 ; Conference date: 25-09-2005 Through 27-09-2005",
}