pyRforest: a comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R.

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Title

pyRforest: a comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R.

Content partner

Massey University

Collection

Massey Research Online

Description

Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, nonlinear, or nonadditive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization. Here, ...

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Format

Research paper

Research format

Journal article

Date created

2024-10-07

Creator

Kolisnik T / Keshavarz-Rahaghi F / Purcell RV / Smith ANH / Silander OK

URL

https://hdl.handle.net/10179/72493

Related subjects

bioinformatics / biomarker identification / genomic data analysis / machine learning / random forest / Genomics / Software / Algorithms / Data Analysis / Humans / Computational Biology / Random Forest

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