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