Determination of optimal recognition algorithms in the two-level system
Pattern Recognition Letters
Optimal linear combinations of neural networks
Neural Networks
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experiments with Classifier Combining Rules
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Optimizing a Multiple Classifier System
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
An Overview and Comparison of Voting Methods for Pattern Recognition
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
A Theoretical and Experimental Analysis of Linear Combiners for Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Trainable fusion rules. I. Large sample size case
Neural Networks
Trainable fusion rules. II. Small sample-size effects
Neural Networks
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Combining classifier with a fuser implemented as a one layer perceptron
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
A boosting approach to multiview classification with cooperation
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Designing fusers on the basis of discriminants – evolutionary and neural methods of training
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
A multi-resolution multi-classifier system for speaker verification
Expert Systems: The Journal of Knowledge Engineering
Classifier fusion with interval-valued weights
Pattern Recognition Letters
Classifier ensemble for an effective cytological image analysis
Pattern Recognition Letters
A survey of multiple classifier systems as hybrid systems
Information Fusion
Cost-sensitive decision tree ensembles for effective imbalanced classification
Applied Soft Computing
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Multiple Classifier Systems are nowadays one of the most promising directions in pattern recognition. There are many methods of decision making by the ensemble of classifiers. The most popular are methods that have their origin in voting method, where the decision of the common classifier is a combination of individual classifiers' outputs. This work presents comparative analysis of some classifier fusion methods based on weighted voting of classifiers' responses and combination of classifiers' discriminant functions. We discus which of presented methods could produce classifier better than Oracle one. Some results of computer experiments carried out on benchmark and computer generated data which confirmed our studies are presented also.