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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.

Functions (8)

fastAdaboost

a Fast Implementation of Adaboost

v1.0.0
MIT + file LICENSE
Authors
Sourav Chatterjee [aut, cre]
Initial release
2016-02-23

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