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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...

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Detaylı Bibliyografya
Yayımlandı:Mach Learn
Asıl Yazarlar: Tsamardinos, Ioannis, Borboudakis, Giorgos, Katsogridakis, Pavlos, Pratikakis, Polyvios, Christophides, Vassilis
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Springer US 2018
Konular:
Online Erişim: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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