Benchmark for filter methods for feature selection in high-dimensional classification data
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Publication:2008133
DOI10.1016/j.csda.2019.106839OpenAlexW2973941913MaRDI QIDQ2008133
Michel Lang, Andrea Bommert, Jörg Rahnenführer, Bernd Bischl, Xu-Dong Sun
Publication date: 22 November 2019
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2019.106839
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Uses Software
Cites Work
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- Wrappers for feature subset selection
- A multicriteria approach to find predictive and sparse models with stable feature selection for high-dimensional data
- Accelerated gradient boosting
- Significance analysis of microarrays applied to the ionizing radiation response
- Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
- 10.1162/153244303322753616
- 10.1162/153244303322753670
- A hybrid filter-based feature selection method via hesitant fuzzy and rough sets concepts
- Use of Ranks in One-Criterion Variance Analysis
- Random forests
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