BaggingRegress function

Standard Bagging ensemble for regression problems.

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)

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

Returns

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