C4.5快速数值阈值搜索算法

Wen-Mau Chong, Chien-Le Goh, Yoon-Teck Bau, K. Lee
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引用次数: 4

摘要

本文提出了一种利用遗传算法技术提高C4.5中阈值搜索过程速度的新算法。在C4.5中的阈值搜索过程中,首先对数值属性中的值进行排序,然后计算每两个连续值之间的中点,并将其指定为候选阈值。这个过程可能很耗时,而且对于大数据并不实用。该算法生成一组可能的阈值,并快速收敛到最佳阈值。实验结果表明,该算法在阈值搜索过程中显著缩短了搜索时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Numerical Threshold Search Algorithm for C4.5
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.
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