RLT - Reinforcement Learning Trees
Random forest with a variety of additional features for regression, classification, and survival analysis. Features include parallel computing with OpenMP, reproducibility with random seeds, variance and confidence band estimations using U-statistics, embedded model for selecting splitting variables and constructing linear combination splits, permutation and distribution-based variable importance, observation and variable weights, and subject tracking across trees.
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openblascppopenmp
7.50 score 10 stars 30 scripts 915 downloadsorthoDr - Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization
Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2017) <doi:10.48550/arXiv.1704.05046> and Zhou & Zhu (2018+) <doi:10.48550/arXiv.1802.06156>. It also serves as a general purpose optimization solver for problems with orthogonality constraints. Parallel computing for approximating the gradient is enabled through `OpenMP'.
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openblascppopenmp
4.28 score 9 stars 1 dependents 14 scripts 202 downloads