A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is introduced in this paper. It is also shown how this method can be used to create ensembles of classifiers. The proposed methods are tested in the context of a handwritten text recognition task. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Günter, S., & Bunke, H. (2003). Fast feature selection in an HMM-based multiple classifier system for handwriting recognition. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. https://doi.org/10.1007/978-3-540-45243-0_38
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