Abstract
In this paper, all of the three relationships of attribute selection standard based on positive region, based on rough bound and based on attribute dependency are firstly analyzed. At the same time, it is proved that the three kinds of selection attribute standards are equivalent to each other. Furthermore the advantages and disadvantages of algorithm for generating decision tree based on positive region are analyzed. Meanwhile, aiming at these disadvantages, a new selection attribute standard based on adjoint positive region is proposed. The decision tree generated with the new standard of attribute selection has the following characteristics: fewer leaf nodes, fewer levels of average depth, better generalization of leaf nodes. Finally an example is used to illustrate the advantages of this new selection attribute standard.
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Acknowledgments
This work was supported by the Beijing talented persons training scientific research project in 2012 (Project name: Algorithm of data mining of incomplete information systems; Project No.2012D005019000001); This work was supported by the importation and development of high-caliber talents project of beijing municipal institutions in 2013 (Project name: Decision tree generation algorithm and its optimization of incomplete information systems); This work was supported by the beijing education committees of increased level of scientific research Project; This work was supported by the beijing philosophical social science project (No.11JGB077); This work was supported by the beijing natural science foundation project (No. 9122003).
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© 2013 Springer-Verlag Berlin Heidelberg
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Gao, J. (2013). Algorithm for Generating Decision Tree Based on Adjoint Positive Region. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_50
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DOI: https://doi.org/10.1007/978-3-642-37502-6_50
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