Fast Estimation Method for the Stability of Ensemble Feature Selectors
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Abstract (arXiv)
It is preferred that feature selectors be textitstable for better interpretabity and robust prediction. Ensembling is known to be effective for improving the stability of feature selectors. Since ensembling is time-consuming, it is desirable to reduce the computational cost to estimate the stability of the ensemble feature selectors. We propose a simulator of a feature selector, and apply it to a fast estimation of the stability of ensemble feature selectors. To the best of our knowledge, this is the first study that estimates the stability of ensemble feature selectors and reduces the computation time theoretically and empirically.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 21 references that are in the map. First posted on arXiv 3 Aug 2021.
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2 of 21 references.
References · 2
- 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
- 2018Hyperparameters and Tuning Strategies for Random Forestcited by 83
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