most citedSubspace Learning for Feature Selection via Rank Revealing QR Factorization: Unsupervised and Hybrid Approaches with Non-negative Matrix Factorization and Evolutionary Algorithm

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cs.LG2022★ 1 cited

Subspace Learning for Feature Selection via Rank Revealing QR Factorization: Unsupervised and Hybrid Approaches with Non-negative Matrix Factorization and Evolutionary Algorithm

Amir Moslemi, Arash Ahmadian

The selection of most informative and discriminative features from high-dimensional data has been noticed as an important topic in machine learning and data engineering. Using matr…