Gene extraction for cancer diagnosis by support vector machines—An improvement
Artificial Intelligence in MedicinePublished 19 July 2005
Te Ming Huang, Vojislav Kecman
Citations87
SJR quartileQ1
SJR score1.40
SNIP1.93
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TL;DR
The results suggest that with a properly chosen parameter C, the extracted genes and the constructed classifier will ensure less overfitting of the training data leading to an increased accuracy in selecting relevant genes.
Abstract
The results suggest that with a properly chosen parameter C, the extracted genes and the constructed classifier will ensure less overfitting of the training data leading to an increased accuracy in selecting relevant genes. Finally, comparison in gene ranking obtained by different algorithms shows that there is a significant consensus among the various algorithms as to which set of genes is relevant.
Keywords
Biochemistry, Genetics and Molecular Biology
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