fastAdaboost: a Fast Implementation of Adaboost
Version 1.0.0

Implements Adaboost based on C++ backend code. This is blazingly fast and especially useful for large, in memory data sets. The package uses decision trees as weak classifiers. Once the classifiers have been trained, they can be used to predict new data. Currently, we support only binary classification tasks. The package implements the Adaboost.M1 algorithm and the real Adaboost(SAMME.R) algorithm.

Getting started

Package details

AuthorSourav Chatterjee [aut, cre]
Date of publication2016-02-28 09:59:32
MaintainerSourav Chatterjee <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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fastAdaboost documentation built on May 30, 2017, 7:02 a.m.