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Very Fast C4.5 Decision Tree Algorithm

机译:快速C4.5决策树算法

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This paper presents a novel algorithm so-called VFC4.5 for building decision trees. It proposes an adaptation of the way C4.5 finds the threshold of a continuous attribute. Instead of finding the threshold that maximizes gain ratio, the paper proposes to simply reduce the number of candidate cut points by using arithmetic mean and median to improve a reported weakness of the C4.5 algorithm when it deals with continuous attributes. This paper will focus primarily on the theoretical aspects of the VFC4.5 algorithm. An empirical trials, using 49 datasets, show that, in most times, the VFC4.5 algorithm leads to smaller decision trees with better accuracy compared to the C4.5 algorithm. VFC4.5 gives excellent accuracy results as C4.5 and it is much faster than the VFDT algorithm.
机译:本文提出了一种用于构建决策树的新颖算法,即所谓的VFC4.5。它提出了对C4.5查找连续属性阈值的方式的一种改进。与其寻找使增益比最大化的阈值,不如通过使用算术平均值和中位数来简单地减少候选切割点的数量,以改善在处理连续属性时C4.5算法的缺点。本文将主要关注VFC4.5算法的理论方面。使用49个数据集进行的经验试验表明,与C4.5算法相比,在大多数情况下,VFC4.5算法可生成较小的决策树,且精度更高。 VFC4.5与C4.5相比,具有出色的精度结果,并且比VFDT算法快得多。

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