DocumentCode :
259529
Title :
Fast Numerical Threshold Search Algorithm for C4.5
Author :
Wen-Mau Chong ; Chien-Le Goh ; Yoon-Teck Bau ; Kian-Chin Lee
Author_Institution :
Fac. of Comput. & Inf., Multimedia Univ., Cyberjaya, Malaysia
fYear :
2014
fDate :
Aug. 31 2014-Sept. 4 2014
Firstpage :
930
Lastpage :
935
Abstract :
This paper presents a new algorithm to improve the speed of threshold searching process in C4.5 by using the technique of genetic algorithms. In the threshold searching process in C4.5, the values in a numerical attribute are sorted first and then the mid-point between every two consecutive values is calculated and designated as a candidate threshold. This process can be time consuming and it is not practical for large data. Our algorithm generates a population of possible thresholds and converges to the best threshold value rapidly. Our experimental results have shown that significant time reduction has been achieved by using our algorithm in threshold searching process.
Keywords :
data mining; decision trees; genetic algorithms; learning (artificial intelligence); pattern classification; C4.5 algorithm; decision tree algorithm; genetic algorithms; large data; machine learning; threshold searching process; Accuracy; Biological cells; Decision trees; Genetic algorithms; Sociology; Statistics; Training; classification; decision tree algorithm; genetic algorithm; numerical attribute;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Applied Informatics (IIAIAAI), 2014 IIAI 3rd International Conference on
Conference_Location :
Kitakyushu
Print_ISBN :
978-1-4799-4174-2
Type :
conf
DOI :
10.1109/IIAI-AAI.2014.183
Filename :
6913427
Link To Document :
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