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Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity
In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers...
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| 出版年: | Front Neurosci |
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| 主要な著者: | , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5775224/ https://ncbi.nlm.nih.gov/pubmed/29379411 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2017.00749 |
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