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It is known that Logistic Regression coupled with Partial Least Squares dimension reduction (PLSDR-LD) is capable of extracting a great deal of useful information for classification from gene expression profile and getting a rather high classification accuracy rate. In this study, we replace the logistic function of Logistic Regression with several functions which are similar to logistic function...
The study was to compare principle component (PC) versus partial least square (PLS) regression, the former unsupervised and the latter supervised gene component analysis, for highly complicated and correlated microarray gene expression profile. Projection of derived classifiers into independent samples for clinical phenotype prediction was evaluated as well. Previous studies had suggested that PLS...
A new gene selection method is proposed based on l1-norm least square regression. The numerical experiment shows that the new approach is, at last comparable to two popular methods: ANOVA and BSS/WSS.
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