Journal ArticleDOI
Methods of combining multiple classifiers and their applications to handwriting recognition
Lei Xu,Adam Krzyżak,Ching Y. Suen +2 more
- Vol. 22, Iss: 3, pp 418-435
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TLDR
On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly.Abstract:
Possible solutions to the problem of combining classifiers can be divided into three categories according to the levels of information available from the various classifiers. Four approaches based on different methodologies are proposed for solving this problem. One is suitable for combining individual classifiers such as Bayesian, k-nearest-neighbor, and various distance classifiers. The other three could be used for combining any kind of individual classifiers. On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly. For example, on the US zipcode database, 98.9% recognition with 0.90% substitution and 0.2% rejection can be obtained, as well as high reliability with 95% recognition, 0% substitution, and 5% rejection. >read more
Citations
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Journal ArticleDOI
A framework for probabilistic combination of multiple classifiers at an abstract level
TL;DR: A framework is proposed to optimally identify a product set of kth-order dependencies, where 1≤ k ⪯- K for the product approximation of the ( K + 1)st-order probability distribution from training samples, and to probabilistically combine multiple decisions by the identified product set, using the Bayesian formalism.
Journal ArticleDOI
Auditory brainstem response classification: A hybrid model using time and frequency features
TL;DR: A hybrid system has been created that emulates the approach used by an audiologist in analysing an ABR waveform and provided a system that enhanced robustness to artefacts while maintaining classification accuracy.
Journal ArticleDOI
Comparing two genetic overproduce-and-choose strategies for fuzzy rule-based multiclassification systems generated by bagging and mutual information-based feature selection
Oscar Cordón,Arnaud Quirin +1 more
TL;DR: An exhaustive study is developed on the potential of the two multicriteria genetic algorithms respectively considering the classical training error and the out-of-bag error fitness functions to design a final multiclassifier with an appropriate accuracy-complexity trade-off.
Journal ArticleDOI
A Lamarckian Hybrid of Differential Evolution and Conjugate Gradients for Neural Network Training
TL;DR: Two schemes that follow the model of Lamarckian evolution and combine differential evolution (DE) with the local optimization algorithm of conjugate gradients (CG) are described, which improve both parents and offspring in a manner that is completely seamless for individuals that survive more than one generation.
Journal ArticleDOI
Teacher-directed learning in view-independent face recognition with mixture of experts using single-view eigenspaces
TL;DR: The experimental results support the claim that directing the experts to a predetermined partitioning of face space improves the performance of the conventional ME for view-independent face recognition.
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