Software

Free R Packages

To lower the threshold to apply our new methods, the customer intelligence cluster of Ghent University develops free R packages for the open source R language (see CRAN website).

Kernel Factory

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, Forthcoming in Expert Systems with Applications.

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. (2012), Binary Quantile Regression: A Bayesian Approach based on the Asymmetric Laplace Density, Journal of Applied Econometrics, 27 (7), 12105-12113.

Ensemble Classifiers for Binary Classification: GAMens (includes GAMbag, GAMrsm and GAMens)

To download the GAMens package: click here.

This package implements the GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification (De Bock et al., 2010). The ensembles implement Bagging (Breiman, 1996), the Random Subspace Method (Ho, 1998), or both, and use Hastie and Tibshirani's (1990) generalized additive models (GAMs) as base classifiers. Once an ensemble classifier has been trained, it can be used for predictions on new data. A function for cross validation is also included.

DE BOCK K.W. et al. (2010), Ensemble classification based on generalized additive models, Computational Statistics and Data Analysis, 54(6), 1535-1546.