AutoFS: Automated Feature Selection via Diversity-Aware Interactive Reinforcement Learning-Reference-Cited by-同舟云学术

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AutoFS: Automated Feature Selection via Diversity-Aware Interactive Reinforcement Learning

Published:2020-11 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Data Mining (ICDM)
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Author:

Fan Wei,Liu Kunpeng,Liu Hao,Wang Pengyang,Ge Yong,Fu Yanjie

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9338245/9338248/09338318.pdf?arnumber=9338318

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. Segmented Glioma Classification Using Radiomics-Based Machine Learning: A Comparative Analysis of Feature Selection Techniques;Lecture Notes in Computer Science;2024

3. Quantitative analysis of potentially toxic elements in soil by XRF based on efficient reinforcement learning and sparse partial least squares;Journal of Analytical Atomic Spectrometry;2024

4. Intelligent charging station recommendations for electric vehicles in the charging market: a fuzzy−deep learning approach;Applications of Deep Machine Learning in Future Energy Systems;2024

5. Beyond Discrete Selection: Continuous Embedding Space Optimization for Generative Feature Selection;2023 IEEE International Conference on Data Mining (ICDM);2023-12-01

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