Nothing
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
Browse package contents
Package details |
|
|---|---|
| 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 CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the fastAdaboost package in your browser
Any scripts or data that you put into this service are public.
