jadonwagstaff/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.

Getting started

Package details

Maintainer
LicenseMIT + file LICENSE
Version0.1.1
URL https://github.com/jadonwagstaff/sboost
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jadonwagstaff/sboost")
jadonwagstaff/sboost documentation built on April 28, 2020, 5:30 p.m.