RPWNSC: Run Purity Weighted Nearest Shrunken Centroid Feature Selection
Provides a classifier independent filter method for high-dimensional
gene-expression feature selection. The Run Purity Weighted Nearest Shrunken
Centroid ('RPWNSC') score ranks genes by multiplying a run based purity score,
which measures the compactness of class labels after sorting samples by each
feature, by a scaled nearest shrunken centroid score, which measures
standardized class centroid separation relative to within class variation.
The top ranked features can then be used with downstream classifiers without
wrapper search, feature clustering, or classifier dependent training.
'Amjad Ali, Zardad Khan, Saeed Aldahmani' (2026) <doi:10.1016/j.mlwa.2026.100947>.
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