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
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On combining classifiers
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References
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Book ChapterDOI
Combining the Classification Results of Independent Classifiers Based on the Dempster/Shafer Theory of Evidence
Eberhard Mandler,Jürgen Schümann +1 more
TL;DR: A procedure is defined that transform the distance measures of different classifiers into confidence values in three subsequent steps and achieves an output vector for each distance classifier which is compatible with statistically adapted classifiers.
Proceedings ArticleDOI
Complementary algorithms for the recognition of totally unconstrained handwritten numerals
TL;DR: Two novel methods for recognizing totally unconstrained handwritten numerals are presented and it is shown that if reliability is of utmost importance, one can avoid substitutions completely and still retain a fairly high recognition rate.
Journal ArticleDOI
A combination of statistical and syntactical pattern recognition applied to classification of unconstrained handwritten numerals
TL;DR: A hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns.
Journal ArticleDOI
Syntactic ECG processing: a review
TL;DR: Although syntactic methods seem suitable to the analysis of waveforms, not much progress has been made in the area of ECG waveforms.
Journal ArticleDOI
An Automated Approach to the Design of Decision Tree Classifiers
TL;DR: This correspondence provides an automated technique for effective decision tree design which relies only on a priori statistics.