C++ Implementation of Component-Wise Boosting

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.


News

compboost 0.1.0

Initial release

  • 19.07.2018
    Compboost now uses sparse matrices for splines to reduce memory load.

  • 29.06.2018
    Compboost API is almost ready to use.

  • 14.06.2018
    Update naming GreedyOptimizer -> OptimizerCoordinateDescent and small typos.

  • 30.03.2018
    Compboost is now ready to do binary classification by using the BernoulliLoss.

  • 29.03.2018
    Upload C++ documentation created by doxygen.

  • 28.03.2018
    P-Splines are now availalbe as baselearner. Additionally the Polynomial and P-Spline learner are speeded up using a more gneeral data structure which stores the inverse once and reuse it for every iteration.

  • 21.03.2018
    New data structure with independent source and target.

  • 01.03.2018
    Compboost should now run stable and without memory leaks.

  • 07.02.2018
    Naming of the C++ classes. Those are matching the R classes now.

  • 29.01.2018
    Update naming to a mroe consistent scheme.

  • 26.01.2018
    Add printer for the classes.

  • 22.01.2018
    Add inbag and out of bag logger.

  • 21.01.2018
    New structure for factorys and baselearner. The function InstantiateData is now member of the factory, not the baselearner. This should also speed up the algorithm, since we don't have to check whether data is instantiated or not. We can do that once within the constructor. Additionally, it should be more clear now what the member does since there is no hacky baselearner helper necessary to instantiate the data.

Reference manual

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install.packages("compboost")

0.1.0 by Daniel Schalk, 4 months ago


Browse source code at https://github.com/cran/compboost


Authors: Daniel Schalk [aut, cre] , Janek Thomas [aut] , Bernd Bischl [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, methods, glue, R6, checkmate

Suggests RcppArmadillo, ggplot2, testthat, rpart, mboost, knitr, rmarkdown, titanic, mlr, gridExtra

Linking to Rcpp, RcppArmadillo


See at CRAN