Geodesic
Handwritten digit recognition by combined classifiers
Kybernetika, Tome 34 (1998) no. 4, p. [381].

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Classifiers can be combined to reduce classification errors. We did experiments on a data set consisting of different sets of features of handwritten digits. Different types of classifiers were trained on these feature sets. The performances of these classifiers and combination rules were tested. The best results were acquired with the mean, median and product combination rules. The product was best for combining linear classifiers, the median for $k$-NN classifiers. Training a classifier on all features did not result in less errors.
Classification : 62H30, 68T10
Keywords: handwritten digits; combined classifiers 
@article{KYB_1998__34_4_a4,
     author = {van Breukelen, M. and Duin, R. P. W. and Tax, D. M. J. and Hartog, J. E. den},
     title = {Handwritten digit recognition by combined classifiers},
     journal = {Kybernetika},
     pages = {[381]},
     publisher = {mathdoc},
     volume = {34},
     number = {4},
     year = {1998},
     zbl = {1274.68403},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_1998__34_4_a4/}
}
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van Breukelen, M.; Duin, R. P. W.; Tax, D. M. J.; Hartog, J. E. den. Handwritten digit recognition by combined classifiers. Kybernetika, Tome 34 (1998) no. 4, p. [381]. http://geodesic.mathdoc.fr/item/KYB_1998__34_4_a4/