An Improved Synthesized Decision Tree Algorithm and its Application

Jian Lin Qiu; Dan Ji; Xiang Gu; Fen Li; Peng He

doi:10.4028/www.scientific.net/AMR.108-111.244

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 108-111An Improved Synthesized Decision Tree Algorithm...

An Improved Synthesized Decision Tree Algorithm and its Application

Abstract:

Decision tree classification is one of the most widely-used methods in data mining which can provide useful decision-making analysis for users. But most of the decision tree methods have some efficiency bottle-necks and can only applied to small-scale datasets. In this paper, we present an new improved synthesized decision tree algorithm named CA which includes three important parts like dimension reduction, pre-clustering and decision tree method, and also give out its formalized specification. Through dimension reduction and synthesized pre-clustering methods, we can optimize the initial dataset and considerably reduce the decision tree’s input computation costs. We also improve the decision tree method by introducing parallel processing concept which can enhance its calculation precision and decision efficiency. This paper applies CA into maize seed breeding and analyzes its efficiency in every part comparing with original methods, and the results shows that CA algorithm is better.

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Periodical:

Advanced Materials Research (Volumes 108-111)

Pages:

244-249

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.108-111.244

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Online since:

May 2010

Authors:

Jian Lin Qiu, Dan Ji, Xiang Gu, Fen Li, Peng He

Keywords:

Clustering, Decision Tree, Dimension Reduction, Formal Specification, Maize Seed Breeding

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References

[1] Ding Rongtao, Ji Xinhao. Study of the Learning Model based on Improved ID3 Algorithm[C]. First International Workshop on Knowledge Discovery and Data Mining, 2008. WKDD 2008. 2008, 391-395.

DOI: 10.1109/wkdd.2008.68

Google Scholar

[2] Jing-Feng Guo, Jing Li. An Efficient Relational Decision Tree Classification Algorithm[C]. Third International Conference on Natural Computation (ICNC 2007), 2007(3), 530-534.

DOI: 10.1109/icnc.2007.195

Google Scholar

[3] Chen Jin, Luo De-lin, Mu Fen-xiang. An Improved ID3 Decision Tree Algorithm[C]. Computer Science & Education. 2009. 4th International Conference on 25-28 July 2009 , 127 - 130.

DOI: 10.1109/iccse.2009.5228509

Google Scholar

[4] Liu Jia, Wang Xinwei. An Improved C4. 5 Algorithm and Algorithm and Experiment Analysis[J]. Computer Applications and Software. 2008, 25(12): 260-262.

Google Scholar

[5] Baoshi Ding, Yongqing Zheng, Shaoyu Zang. A New Decision Tree Algorithm Based on Rough Set Theory[C]. Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on Volume 2, 18-19 July 2009 Page(s): 326 - 329.

DOI: 10.1109/apcip.2009.216

Google Scholar

[6] Christophe Marsala. A Fuzzy Decision Tree Based Approach to Characterize Medical Data [C]. FUZZ-IEEE 2009. IEEE International Conference on 20-24 Aug. 2009 Page(s): 1332 - 1337.

DOI: 10.1109/fuzzy.2009.5277106

Google Scholar

[7] ZHAO Jing-xian1; 2; NI Chun-peng1; ZHAN Yuan-rui1. Combined Optimization Decision Tree Algorithm Suitable for Large Scale Data-base [J]. Systems Engineering and Electronics. 2009, 31(3): 583-587.

Google Scholar