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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Detalles Bibliográficos
Autores principales: Tsamardinos, Ioannis, Borboudakis, Giorgos, Katsogridakis, Pavlos, Pratikakis, Polyvios, Christophides, Vassilis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399683/
https://www.ncbi.nlm.nih.gov/pubmed/30906113
http://dx.doi.org/10.1007/s10994-018-5748-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399683/
https://www.ncbi.nlm.nih.gov/pubmed/30906113
http://dx.doi.org/10.1007/s10994-018-5748-7

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