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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 3 | Page No.: 528-534
DOI: 10.3923/jas.2009.528.534
 
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Development and Test of Fixed Average K-means Base Decision Trees Grouping Method by Improving Decision Tree Clustering Method

Jai-Houng Leu, Chih-Yao Lo and Chi-Hau Liu

Abstract:
New analytical methods and tools which were called FAKDT (Fixed Average K-means base Decision Trees) on human performance have been developed and they make us look at the Enterprise in different aspects in this study. Decision Tree Clustering Method is one of the data mining methods that have been applied widely in different fields to analyze a large amount of data in recent years. Generally speaking, in the human resource incubation of an enterprise, if employees of high learning potential, high stability and high emotional quotient are selected, the return of investment in human resources will be more apparent. If employees of the above mentioned traits can be well utilized and incubated, the industry competitiveness of the enterprise will be enhanced effectively. From the personality specialty point of view, its function is to predict the efficiency of the personal achievement in correlation to his some implying personality specialties (blood group, constellation, etc.). The main purpose of this research is to get the useful information and important message about human performance from their historical records with this method. The Decision Tree Clustering Method data mining skills were improved and applied to get the critical factors that affect the human traits for its feasibility in this study.
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How to cite this article:

Jai-Houng Leu, Chih-Yao Lo and Chi-Hau Liu, 2009. Development and Test of Fixed Average K-means Base Decision Trees Grouping Method by Improving Decision Tree Clustering Method. Journal of Applied Sciences, 9: 528-534.

DOI: 10.3923/jas.2009.528.534

URL: https://scialert.net/abstract/?doi=jas.2009.528.534

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