On synthetic data, PCA reconstruction loss yields compact feature subsets whose supervised test accuracy matches direct optimization, while silhouette score strongly biases toward trivial low-cardinality solutions.
Anunsupervisedapproach to feature discretization and selection.Pattern Recognition, 45(9):3048– 3060, September 2012
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Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection
On synthetic data, PCA reconstruction loss yields compact feature subsets whose supervised test accuracy matches direct optimization, while silhouette score strongly biases toward trivial low-cardinality solutions.