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A greedy feature selection algorithm for Big Data of high dimensionality
We present the Parallel, Forward–Backward with Pruning (PFBP) algorithm for feature selection (FS) for Big Data of high dimensionality. PFBP partitions the data matrix both in terms of rows as well as columns. By employing the concepts of p-values of conditional independence tests and meta-analysis...
Guardat en:
| Publicat a: | Mach Learn |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Springer US
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6399683/ https://ncbi.nlm.nih.gov/pubmed/30906113 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10994-018-5748-7 |
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