Package: RPWNSC 0.1.0

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>.

Authors:Amjad Ali [aut, cre], Zardad Khan [aut], Saeed Aldahmani [aut]