TAN与马尔可夫算法应用的比较

2011 International Conference on Electrical and Control Engineering Pub Date : 2011-10-24 DOI:10.1109/ICECENG.2011.6057533

Dongdong Xie, Wenning Hao, Gang Chen, Dawei Jin, Shuining Zhao

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摘要

基于贝叶斯网络的TAN分类器是常用的分类方法。本文采用基于贝叶斯网络、马尔可夫网络和神经网络的TAN分类器分别对消费者信息数据和重复数据进行分类，并对结果进行比较。发现在对大量数据进行分类时，使用TAN分类器在效率和精度上有一定的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The comparison of application of TAN and Markov

The TAN classifiers based on bayes network are often used in classifying. This paper use TAN classifiers based on bayes network, Markov network and Neural Networks to classify the data of consumers' information and the reduplicated data separately, and compare the results. And found there are some advantages in efficiency and precision to use TAN classifiers in classifying of a great deal of data.

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2011 International Conference on Electrical and Control Engineering

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