Neural Network Ensembles to Determine Growth Multi-classes in Predictive Microbiology
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- Áreas de investigación:
- Año:
- 2012
- Tipo de publicación:
- Artículo en conferencia
- Palabras clave:
- Negative Correlation Learning, Neural Networks, Ordinal Regression
- Autores:
-
- Fernandez-Navarro, Francisco
- Chen, Huanhuan
- Gutiérrez, Pedro Antonio
- Hervás-Martínez, César
- Yao, Xin
- Título del libro:
- 7th International Conference on Hybrid Artificial Intelligence Systems (HAIS2012)
- Páginas:
- 308-318
- Abstract:
- This paper evaluates the performance of different ordinal regression, nominal classifiers and regression models when predicting probability growth of the Staphylococcus Aureus microorganism. The prediction problem has been formulated as an ordinal regression problem, where the different classes are associated to four values in an ordinal scale. The results obtained in this paper present the Negative Correlation Learning as the best tested model for this task. In addition, the use of the intrinsic ordering information of the problem is shown to improve model performance.
