sboost
Machine Learning with AdaBoost on Decision Stumps
v0.1.2
·
May 26, 2022
·
MIT + file LICENSE
Description
Creates classifier for binary outcomes using Adaptive Boosting (AdaBoost) algorithm on decision stumps with a fast C++ implementation. For a description of AdaBoost, see Freund and Schapire (1997) <doi:10.1006/jcss.1997.1504>. This type of classifier is nonlinear, but easy to interpret and visualize. Feature vectors may be a combination of continuous (numeric) and categorical (string, factor) elements. Methods for classifier assessment, predictions, and cross-validation also included.
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| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
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| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
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| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |