Floating search and conditional independence testing for causal feature selection
The curse of dimensionality and over-fitting problems are usually associated with high-dimensional data. Feature selection is one method that can overcome these problems. This paper proposes floating search and conditional independence testing as a causal feature selection algorithm (FSCI). FSCI u...
| 主要な著者: | , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Prince of Songkla University
2021-12-01
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| シリーズ: | Songklanakarin Journal of Science and Technology (SJST) |
| 主題: | |
| オンライン･アクセス: | https://rdo.psu.ac.th/sjst/journal/43-6/39.pdf |