REBAGG: REsampled BAGGing for Imbalanced Regression Tasks - LIDTA 2018
This repository has all the code used in the experiments carried out in the paper “REBAGG: REsampled BAGGing for Imbalanced Regression” [1].
This repository is organized as follows:
The experimental design was implemented in R language. Both code and data are in a format suitable for R environment.
In order to replicate these experiments you will need a working installation
of R. Check [https://www.r-project.org/] if you need to download and install it.
In your R installation you also need to install the following additional R packages:
All the above packages with the exception of uba, can be installed from CRAN Repository directly as any “normal” R package. Essentially you need to issue the following command within R:
install.packages(c("DMwR", "performanceEstimation", "UBL", "randomForest", "e1071", "earth", "rpart", "gbm"))
The package uba needs to be installed from a tar.gz file that you
can download from http://www.dcc.fc.up.pt/~rpribeiro/uba/.
Download the tar.gz file into your folder and then issue:
install.packages("uba_0.7.8.tar.gz",repos=NULL,dependencies=T)
Check the other README files in each folder to see more detailed instructions on how to run the experiments.
[1] Branco, P. and Torgo, L. and Ribeiro, R.P. (2018) “REBAGG: REsampled BAGGing for Imbalanced Regression” LIDTA2018: 2nd International Workshop on Learning with Imbalanced Domains: Theory and Applications (Co-located with ECML/PKDD 2018) Dublin, Ireland (to appear)