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Unsupervised Feature Selection Using Local Intrinsic Dimensionality -- Extended Version
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feature_selectionunsupervised_learningdimensionality_reduction
2610.40736
Builder Relevance
1h ago80%
Abstract
This paper presents LIDFS, an unsupervised feature selection method that improves learning efficiency by selecting features based on their local intrinsic dimensionality.
Reality Card
Core Claim
LIDFS outperforms classic and state-of-the-art feature selection methods in both supervised and unsupervised evaluations while running faster than its closest competitor.
Method / Result
LIDFS ranks first in supervised evaluations across 23 high-dimensional datasets.
Limitations
The method's performance may vary with neighborhood size, which could affect reproducibility.
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