@inproceedings{40ee39ff24c949598001d7fa5e551c34,
title = "Transformation-based hierarchical decision rules using genetic algorithms and its application to handwriting recognition domain",
abstract = "This paper describes a new approach based on Transformation-Based Learning for extracting hierarchical decision rules. Genetic algorithms are adapted to establish the context environment for transformation operation and the transformation operation can lengthen the life cycle of {"}good{"} candidate rules. The experiments are conducted on iris, wine and glass datasets with a 10-fold cross validation setup. The results show that transformation operation can improve the precision of the classifier with a smaller number of rules and generations than hierarchical decision rules. The approach also works well in touching block extraction of Chinese handwritten text.",
author = "Tonghua Su and Tianwen Zhang and Hujie Huang and Guixiang Xue and Zheng Zhao",
year = "2008",
doi = "10.1109/CEC.2008.4630911",
language = "英语",
isbn = "9781424418237",
series = "2008 IEEE Congress on Evolutionary Computation, CEC 2008",
pages = "951--956",
booktitle = "2008 IEEE Congress on Evolutionary Computation, CEC 2008",
note = "2008 IEEE Congress on Evolutionary Computation, CEC 2008 ; Conference date: 01-06-2008 Through 06-06-2008",
}