Heterogeneous versus Homogeneous Machine Learning Ensembles

Aleksandra Petrakova, Michael Affenzeller, Galina Merkurjeva


The research demonstrates efficiency of the heterogeneous model ensemble application for a cancer diagnostic procedure. Machine learning methods used for the ensemble model training are neural networks, random forest, support vector machine and offspring selection genetic algorithm. Training of models and the ensemble design is performed by means of HeuristicLab software. The data used in the research have been provided by the General Hospital of Linz, Austria.


Classification task; ensemble modelling; machine learning; majority voting

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Copyright (c) 2015 Aleksandra Petrakova, Michael Affenzeller, Galina Merkurjeva

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