souravc83/fastAdaboost: a Fast Implementation of Adaboost
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
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Package details |
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| Author | Sourav Chatterjee [aut, cre] |
| Maintainer | Sourav Chatterjee <souravc83@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.0.0 |
| URL | https://github.com/souravc83/fastAdaboost |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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