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Authors: Cristiano Leite Castro 1 and Antônio Padua Braga 2

Affiliations: 1 Federal University of Lavras, Brazil ; 2 Federal University of Minas Gerais, Brazil

Keyword(s): Multi-Layer Perceptron (MLP), Backpropagation algorithm, ROC analysis, Imbalanced data sets, Costsensitive learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computational Neuroscience ; Computer-Supported Education ; Data Manipulation ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Learning Paradigms and Algorithms ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neuroinformatics and Bioinformatics ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Supervised and Unsupervised Learning ; Theory and Methods

Abstract: In order to control the trade-off between sensitivity and specificity of MLP binary classifiers, we extended the Backpropagation algorithm, in batch mode, to incorporate different misclassification costs via separation of the global mean squared error between positive and negative classes. By achieving different solutions in ROC space, our algorithm improved the MLP classifier performance on imbalanced training sets. In our experiments, standard MLP and SVM algorithms were compared to our solution using real world imbalanced applications. The results demonstrated the efficiency of our approach to increase the number of correct positive classifications and improve the balance between sensitivity and specificity.

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Paper citation in several formats:
Leite Castro, C. and Padua Braga, A. (2009). ARTIFICIAL NEURAL NETWORKS LEARNING IN ROC SPACE. In Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICNC; ISBN 978-989-674-014-6; ISSN 2184-3236, SciTePress, pages 484-489. DOI: 10.5220/0002324404840489

@conference{icnc09,
author={Cristiano {Leite Castro}. and Antônio {Padua Braga}.},
title={ARTIFICIAL NEURAL NETWORKS LEARNING IN ROC SPACE},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICNC},
year={2009},
pages={484-489},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002324404840489},
isbn={978-989-674-014-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICNC
TI - ARTIFICIAL NEURAL NETWORKS LEARNING IN ROC SPACE
SN - 978-989-674-014-6
IS - 2184-3236
AU - Leite Castro, C.
AU - Padua Braga, A.
PY - 2009
SP - 484
EP - 489
DO - 10.5220/0002324404840489
PB - SciTePress