一种改进的决策树分类算法研究

Wenyi Xu
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引用次数: 0

摘要

本文详细介绍了分类的数据挖掘算法,然后将分类算法与增量学习技术相结合,提出了一种增量决策树算法来解决增量学习问题,并对该算法的实验数据进行了分析。本文采用ID3和C4.5算法进行详细研究。根据两种算法,结合贝叶斯分类算法的增量学习特性,提出了一种增量决策树算法,并通过实验数据分析。该算法很好地解决了决策树算法的增量学习问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on an Improved Decision Tree Classification Algorithm
In the paper, with the introduction of data mining algorithm of the classification in detail, and then combining the classification algorithm and incremental learning technology, an incremental decision tree algorithm is proposed to solve the problem of incremental learning and analysis the experimental data for this algorithm. The paper used ID3 and C4.5 algorithm for detailed research. According to two algorithms, combining Bayesian classification algorithm’s incremental learning characteristic, the paper proposed an incremental decision tree algorithm , and by the analysis of experimental data. This algorithm can solve the incremental learning problem of the decision tree algorithm very well.
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