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Locally Learning Biomedical Data Using Diffusion Frames
Diffusion geometry techniques are useful to classify patterns and visualize high-dimensional datasets. Building upon ideas from diffusion geometry, we outline our mathematical foundations for learning a function on high-dimension biomedical data in a local fashion from training data. Our approach is...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Mary Ann Liebert, Inc.
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3493038/ https://ncbi.nlm.nih.gov/pubmed/23101786 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1089/cmb.2012.0187 |
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