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Found 3 papers, 3 papers with code
Low-rank Dictionary Learning for Unsupervised Feature Selection
Due to the hardship of labeling on these datasets, there are a variety of approaches on feature selection process in an unsupervised setting by considering some important characteristics of data.
Similarity Preserving Unsupervised Feature Selection based on Sparse Learning
Various feature selection methods have been recently proposed on different applications to reduce the computational burden of machine learning algorithms as well as the complexity of learned models.
Unsupervised Feature Selection based on Adaptive Similarity Learning and Subspace Clustering
Feature selection methods have an important role on the readability of data and the reduction of complexity of learning algorithms.
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