Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Combining One-Class Classifiers
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Information Analysis of Multiple Classifier Fusion
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Extraction of Binary Features by Probabilistic Neural Networks
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Hindi paired word recognition using probabilistic neural network
International Journal of Computational Intelligence Studies
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The statistical pattern recognition based on Bayes formula implies the concept of mutually exclusive classes. This assumption is not applicable when we have to identify some non-exclusive properties and therefore it is unnatural in biological neural networks. Considering the framework of probabilistic neural networks we propose statistical identification of non-exclusive properties by using one-class classifiers.