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The work presented in this paper describes how sub-space grids can be employed to extract rules for micro array classification. The paper first describes principal component analysis (PCA) algorithm for obtaining sub-space grids from the projected low dimensional space. A recursive procedure is then used to obtain rules where sub-space grids form premises of rules. The extracted set of rules is evaluated...
Feature ranking, which ranks features via their individual importance, is one of the frequently used feature selection techniques. Traditional feature ranking criteria are apt to produce inconsistent ranking results even with light perturbations in training samples when applied to high dimensional and small-sized gene expression data. A widely used strategy for solving the inconsistencies is the multi-criterion...
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