| BaggingRegress {UBL} | R Documentation |
Standard Bagging ensemble for regression problems.
Description
This function handles regression problems through ensemble learning. A given number of weak learners selected by the user are trained on bootstrap samples of the training data provided.
Usage
BaggingRegress(form, train, nmodels, learner, learner.pars,
aggregation = "Average", quiet=TRUE)
Arguments
form |
A formula describing the prediction problem. |
train |
A data frame containing the training (imbalanced) data set. |
nmodels |
A numeric indicating the number of models to train. |
learner |
The learning algorithm to be used as weak learner. |
learner.pars |
A named list with the parameters selected for the learner. |
aggregation |
charater specifying the method used for aggregating the results obtained by the individual learners. For now, the only method available is by averaging the models predictions. |
quiet |
logical specifying if development should be shown or not.Defaults to TRUE |
Value
The function returns an object of class BagModel.
Author(s)
Paula Branco paobranco@gmail.com, Rita Ribeiro rpribeiro@dcc.fc.up.pt and Luis Torgo ltorgo@dcc.fc.up.pt