CRAN/E | sboost

sboost

Machine Learning with AdaBoost on Decision Stumps

Installation

About

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.

github.com/jadonwagstaff/sboost
Bug report File report

Key Metrics

Version 0.1.2
R ≥ 3.4.0
Published 2022-05-26 865 days ago
Needs compilation? yes
License MIT
License File
CRAN checks sboost results

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Maintainer

Maintainer

Jadon Wagstaff

Authors

Jadon Wagstaff

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

sboost archive

Depends

R ≥ 3.4.0

Imports

dplyr ≥ 0.7.6
rlang ≥ 0.2.1
Rcpp ≥ 0.12.17
stats ≥ 3.4

Suggests

testthat

LinkingTo

Rcpp ≥ 0.12.17