Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 135-142 |
| Journal | Information Technology and Management Science |
| Volume | 18 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Classification task
- ensemble modelling
- machine learning
- majority voting
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