ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
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DOI: 10.18637/jss.v077.i01
Abstract: We introduce the C++ application and R package ranger. The software is a fast implementation of random forests for high dimensional data. Ensembles of classification, regression and survival trees are supported. We describe the implementation,… read more here.
Keywords: forests high; implementation; implementation random; random forests ... See more keywords
Improved Variable Forgetting Factor Proportionate RLS Algorithm with Sparse Penalty and Fast Implementation Using DCD Iterations
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DOI: 10.23919/jcc.ja.2022-0367
Abstract: the proportionate recursive least squares (PRLS) algorithm has shown faster convergence and better performance than both proportionate updating (PU) mechanism based least mean squares (LMS) algorithms and RLS algorithms with a sparse regularization term. In… read more here.
Keywords: proportionate; sparse penalty; fast implementation; forgetting factor ... See more keywords