Heterogeneous versus Homogeneous Machine Learning Ensembles
2015
Aleksandra Petrakova,
Michael Affenzeller,
Gaļina 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.
Atslēgas vārdi
Classification task, ensemble modelling, machine learning, majority voting.
Petrakova, A., Affenzeller, M., Merkurjeva, G. Heterogeneous versus Homogeneous Machine Learning Ensembles. Information Technology and Management Science. Nr.18, 2015, 135.-140.lpp. ISSN 2255-9086. e-ISSN 2255-9094.
Publikācijas valoda
English (en)