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compboost (version 0.1.0)

C++ Implementation of Component-Wise Boosting

Description

C++ implementation of component-wise boosting implementation of component-wise boosting written in C++ to obtain high runtime performance and full memory control. The main idea is to provide a modular class system which can be extended without editing the source code. Therefore, it is possible to use R functions as well as C++ functions for custom base-learners, losses, logging mechanisms or stopping criteria.

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Version

Install

install.packages('compboost')

Monthly Downloads

3

Version

0.1.0

License

MIT + file LICENSE

Maintainer

Daniel Schalk

Last Published

October 28th, 2018

Functions in compboost (0.1.0)

Compboost_internal

Main Compboost Class

Logger class to log the out of bag risk

0-1 Loss for binary classification derived of the binomial distribution

Create LossCustom by using R functions.

Create custom cpp losses by using cpp functions and external pointer.

Quadratic loss for regression tasks.

getCustomCppExample

Get example C++ script to define a custom cpp logger

Wrapper to boost p spline models for each feature.

BaselearnerCustomCpp

Create custom cpp base-learner factory by using cpp functions and external pointer.

OptimizerCoordinateDescent

Greedy Optimizer

Wrapper to boost linear models for each feature.

LoggerInbagRisk

Logger class to log the inbag risk

LoggerIteration

Logger class to log the current iteration

BaselearnerCustom

Create custom base-learner factory by using R functions.

In memory data class to store data in RAM

BaselearnerPSpline

Base-learner factory to do non-parametric B or P-spline regression

Logger class to log the elapsed time

BaselearnerPolynomial

Base-learner factory to make polynomial regression

Absolute loss for regression tasks.

Logger list class to collect all loggers

BlearnerFactoryList

Base-learner factory list to define the set of base-learners