1. A method in a data processing system for generating a recognition data model set comprising: receiving first and second class dependent data models sets based on corresponding first and second class training data sets, each set of training data originating from a subset of all the training data; receiving a class independent data model set based on all training data, each data model set comprising a plurality of data models; wherein each data model in one data model set being part of a group of corresponding data models from the other data model sets; comparing the fit of each group of corresponding class dependent data models to the training data and the fit of the corresponding independent data model to the training data; and selecting, for all groups of corresponding data models, the group of corresponding class dependent data models or the corresponding independent data model based on the fit comparison and adding the selected data model or models to a final data model.