Accelerated learning in layered neural networks
Complex Systems
Connectionist learning procedures
Machine learning: paradigms and methods
Links between Markov models and multilayer perceptrons
Advances in neural information processing systems 1
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
A continuous speech recognition system embedding MLP into HMM
Advances in neural information processing systems 2
Advances in neural information processing systems 2
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Context Dependent Phoneme Recognition
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
State-Space Model Based Labeling of Speech Signals
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
A Discriminative Segmental Speech Model and Its Application to Hungarian Number Recognition
TDS '00 Proceedings of the Third International Workshop on Text, Speech and Dialogue
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
Real-Time Gesture Recognition by Means of Hybrid Recognizers
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
A Neural Network-Hidden Markov Model Hybrid for Cursive Word Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Classifier ensembles: Select real-world applications
Information Fusion
Wavelet transformation and cluster ensemble for gene expression analysis
International Journal of Bioinformatics Research and Applications
Risk-sensitive loss functions for sparse multi-category classification problems
Information Sciences: an International Journal
Adaptive voting rules for k-nearest neighbors classifiers
Neural Computation
Learning of Bayesian Discriminant Functions by a Layered Neural Network
Neural Information Processing
Diverse Evolutionary Neural Networks Based on Information Theory
Neural Information Processing
Multi-category Bayesian Decision by Neural Networks
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Reverse Correlation for Analyzing MLP Posterior Features in ASR
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Particle swarm optimized multiple regression linear model for data classification
Applied Soft Computing
A neural network approach to normality testing
Intelligent Data Analysis
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Automatic detection system for cough sounds as a symptom of abnormal health condition
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Classification of graphical data made easy
Neurocomputing
Simplifying Particle Swarm Optimization
Applied Soft Computing
An investigation of neural network classifiers with unequal misclassification costs and group sizes
Decision Support Systems
Bayesian decision theory on three-layer neural networks
Neurocomputing
Classifier combination based on confidence transformation
Pattern Recognition
Multicategory bayesian decision using a three-layer neural network
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
The mee principle in data classification: A perceptron-based analysis
Neural Computation
Bayesian learning of neural networks adapted to changes of prior probabilities
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Estimating the class posterior probabilities in protein secondary structure prediction
PRIB'11 Proceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics
Texture segmentation using neural networks and multi-scale wavelet features
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Discriminant analysis by a neural network with mahalanobis distance
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Neural network based texture segmentation using a markov random field model
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Neural networks combination by fuzzy integral in clinical electromyography
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
A novel parameter refinement approach to one class support vector machine
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
A new algorithm for learning mahalanobis discriminant functions by a neural network
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Neural network detectors for composite hypothesis tests
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Structural and Multidisciplinary Optimization
WeAidU-a decision support system for myocardial perfusion images using artificial neural networks
Artificial Intelligence in Medicine
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
International Journal of Speech Technology
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods
Journal of Automated Reasoning
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Many neural network classifiers provide outputs which estimate Bayesian a posteriori probabilities. When the estimation is accurate, network outputs can be treated as probabilities and sum to one. Simple proofs show that Bayesian probabilities are estimated when desired network outputs are 1 of M (one output unity, all others zero) and a squared-error or cross-entropy cost function is used. Results of Monte Carlo simulations performed using multilayer perceptron (MLP) networks trained with backpropagation, radial basis function (RBF) networks, and high-order polynomial networks graphically demonstrate that network outputs provide good estimates of Bayesian probabilities. Estimation accuracy depends on network complexity, the amount of training data, and the degree to which training data reflect true likelihood distributions and a priori class probabilities. Interpretation of network outputs as Bayesian probabilities allows outputs from multiple networks to be combined for higher level decision making, simplifies creation of rejection thresholds, makes it possible to compensate for differences between pattern class probabilities in training and test data, allows outputs to be used to minimize alternative risk functions, and suggests alternative measures of network performance.