search for: baselearner

Hi all, First of all, I'm a novice R user (less that a week), so perhaps my code isn't very efficient. Using the MBoost package I created a model using the following command and saved it to a file for later use: model <- gamboost(fpfm,data=SampleClusterData,baselearner="bbs") # Creating a model save(model,file="model.RData") # Saving a model After this, during a new R session, I want to deploy this model: setwd("Q:/Program Files/R/library/mboost/data") NewData <- read.table("NewData.txt",header=TRUE,sep=,",&quot...

...the training data ranges from 3 to 8 on a numeric scale. In order to restrict the predicted values to the value range from 3 to 8 I limit the feature space of the prediction data on the minima and maxima of the training data for every predictor variable before applying the model on the new data. As baselearner in mboost I use splines ("bbs"): mod <- mboost(MF ~ bbs(predictor1) + bbs(predictor2) + bbs(...), data = train) I wonder why there are negative values when applying the model on new data, because both, training and prediction data have the same value ranges in the predictor variables...