R-universe - jadonwagstaff (Jadon Wagstaff)

remap - Regional Spatial Modeling with Continuous Borders

Automatically creates separate regression models for different spatial regions. The prediction surface is smoothed using a regional border smoothing method. If regional models are continuous, the resulting prediction surface is continuous across the spatial dimensions, even at region borders. Methodology is described in Wagstaff and Bean (2023) <doi:10.32614/RJ-2023-004>.

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4.51 score 1 stars 65 scripts 286 downloads

sboost - Machine Learning with AdaBoost on Decision Stumps

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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cpp

3.00 score 2 stars 8 scripts 234 downloads