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The Sparse MLE for Ultra-High-Dimensional Feature Screening
Feature selection is fundamental for modeling the high dimensional data, where the number of features can be huge and much larger than the sample size. Since the feature space is so large, many traditional procedures become numerically infeasible. It is hence essential to first remove most apparentl...
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| Yayımlandı: | J Am Stat Assoc |
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| Asıl Yazarlar: | , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
2014
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4219371/ https://ncbi.nlm.nih.gov/pubmed/25382886 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2013.879531 |
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