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.
BaggingRegress(form, train, nmodels, learner, learner.pars,
aggregation = "Average", quiet=TRUE)The function returns an object of class BagModel.
A formula describing the prediction problem.
A data frame containing the training (imbalanced) data set.
A numeric indicating the number of models to train.
The learning algorithm to be used as weak learner.
A named list with the parameters selected for the learner.
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.
logical specifying if development should be shown or not.Defaults to TRUE
Paula Branco paobranco@gmail.com, Rita Ribeiro rpribeiro@dcc.fc.up.pt and Luis Torgo ltorgo@dcc.fc.up.pt