mlsanityData to 14 Oct 2026

Survey on Feature Selection

arXiv 1510.02892 ↗First posted 10 Oct 2015cs.LGcited by 25

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Abstract (arXiv)

Feature selection plays an important role in the data mining process. It is needed to deal with the excessive number of features, which can become a computational burden on the learning algorithms. It is also necessary, even when computational resources are not scarce, since it improves the accuracy of the machine learning tasks, as we will see in the upcoming sections. In this review, we discuss the different feature selection approaches, and the relation between them and the various machine learning algorithms.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Oct 2015.

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Citing papers per year: 2021: 7; 2022: 4; 2023: 4; 2024: 8; 2025: 2.

25 papers.

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  1. 2023Probabilistic Bilevel Coreset Selectioncited by 27
  2. 2022On Supervised Feature Selection from High Dimensional Feature Spacescited by 23
  3. 2022Feature Selection on Quantum Computerscited by 21
  4. 2023Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisitioncited by 19
  5. 2022Where to Pay Attention in Sparse Training for Feature Selection?cited by 15
  6. 2024Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agentcited by 15
  7. 2021Federated Feature Selection for Cyber-Physical Systems of Systemscited by 11
  8. 2024ICE-SEARCH: A Language Model-Driven Feature Selection Approachcited by 8
  9. 2023Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Taskscited by 5
  10. 2024Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalancecited by 5
  11. 2023Topological Feature Selectioncited by 3
  12. 2024Distribution Guided Active Feature Acquisitioncited by 3
13 more
  1. 2021Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methodscited by 2
  2. 2021Automated Supervised Feature Selection for Differentiated Patterns of Carecited by 2
  3. 2021A Novel Bio-Inspired Hybrid Multi-Filter Wrapper Gene Selection Method with Ensemble Classifier for Microarray Datacited by 1
  4. 2024Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivativescited by 1
  5. 2024Effect sizes as a statistical feature-selector-based learning to detect breast cancercited by 1
  6. 2025BOLIMES: Boruta and LIME optiMized fEature Selection for Gene Expression Classificationcited by 1
  7. 2021Hierarchical Subspace Learning for Dimensionality Reduction to Improve Classification Accuracy in Large Data Setscited by 0
  8. 2021Machine Learning based CVD Virtual Metrology in Mass Produced Semiconductor Processcited by 0
  9. 2021Accuracy analysis of Educational Data Mining using Feature Selection Algorithmcited by 0
  10. 2022Sparsity-based Feature Selection for Anomalous Subgroup Discoverycited by 0
  11. 2024Estimate the building height at a 10-meter resolution based on Sentinel datacited by 0
  12. 2024UQ of 2D Slab Burner DNS: Surrogates, Uncertainty Propagation, and Parameter Calibrationcited by 0
  13. 2025Streamlining HTTP Flooding Attack Detection through Incremental Feature Selectioncited by 0