CloudForest: A Scalable and Efficient Random Forest Implementation for Biological Data.
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ABSTRACT:
SUBMITTER: Bressler R
PROVIDER: S-EPMC4692062 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
CloudForest: A Scalable and Efficient Random Forest Implementation for Biological Data.
Bressler Ryan R Kreisberg Richard B RB Bernard Brady B Niederhuber John E JE Vockley Joseph G JG Shmulevich Ilya I Knijnenburg Theo A TA
PloS one 20151217 12
Random Forest has become a standard data analysis tool in computational biology. However, extensions to existing implementations are often necessary to handle the complexity of biological datasets and their associated research questions. The growing size of these datasets requires high performance implementations. We describe CloudForest, a Random Forest package written in Go, which is particularly well suited for large, heterogeneous, genetic and biomedical datasets. CloudForest includes severa ...[more]
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