Free Open-Source R Packages
To lower the threshold to apply our new methods, the Data Analytics Cluster of Ghent University develops free R packages for the open source R language (see CRAN website).
To download the hybridEnsemble package: click here.
This package contains functions to build and deploy an ensemble consisting of eight different sub-ensembles: bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, and bagged k-nearest neighbors. Functions to cross-validate the Hybrid Ensemble and plot and summarize the results are also provided. There is also a function to assess the importance of the predictors.
The paper linked to this package is still under review.
To download the kernelFactory package: click here.
This R package implements classification based on an ensemble of kernel machines. Below you find the reference:
BALLINGS M. & VAN DEN POEL D. (2013), Kernel Factory: An ensemble of Kernel Machines, Expert Systems with Applications, 40 (8), 2904-2913.
Bayesian Quantile Regression: bayesQR
To download the bayesQR package: click here.
This R package implements bayesian quantile regression using the asymmetric Laplace distribution, both continuous as well as binary dependent variables are supported. The package consists of implementations of the methods of Yu & Moyeed (2001) and Benoit & Van den Poel (2011). Below you find the latter reference:
BENOIT D. & VAN DEN POEL D. (2016), The BayesQR Package, Forthcoming in Journal of Statistical Software.
BENOIT D. & VAN DEN POEL D. (2012), Binary Quantile Regression: A Bayesian Approach based on the Asymmetric Laplace Density, Journal of Applied Econometrics, 27 (7), 12105-12113.