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Sparse Exponential Family Principal Component Analysis
We propose a Sparse exponential family Principal Component Analysis (SePCA) method suitable for any type of data following exponential family distributions, to achieve simultaneous dimension reduction and variable selection for better interpretation of the results. Because of the generality of expon...
Tallennettuna:
| Julkaisussa: | Pattern Recognit |
|---|---|
| Päätekijät: | , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2016
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5210214/ https://ncbi.nlm.nih.gov/pubmed/28066030 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patcog.2016.05.024 |
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