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cff-version: 1.2.0
message: 'To cite package "fastAdaboost" in publications use:'
type: software
license: MIT
title: 'fastAdaboost: a Fast Implementation of Adaboost'
version: 1.0.0
doi: 10.32614/CRAN.package.fastAdaboost
abstract: 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.
authors:
- family-names: Chatterjee
  given-names: Sourav
  email: souravc83@gmail.com
repository: https://rickhelmus.r-universe.dev
repository-code: https://github.com/souravc83/fastAdaboost
commit: f331ff8ccfe2e7f318448a29bc72af646dfaf2c1
url: https://github.com/souravc83/fastAdaboost
date-released: '2016-02-23'
contact:
- family-names: Chatterjee
  given-names: Sourav
  email: souravc83@gmail.com