利用Kullback-Leibler散度挖掘消极和积极影响规则

2007 International Multi-Conference on Computing in the Global Information Technology (ICCGI'07) Pub Date : 2007-03-04 DOI:10.1109/ICCGI.2007.38

L. N. Alachaher, S. Guillaume

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引用次数: 5

摘要

本文描述了一种基于统计不相似度度量(Kullback Leibler散度)和列联表之间的协调来挖掘消极和积极定量影响规则的新方法。这种协调确定了重要的正相关性和负相关性，并能够提取相关的影响规则。

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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Mining Negative and Positive Influence Rules Using Kullback-Leibler Divergence

This paper describes a new method for mining negative and positive quantitative influence rules based on a coordination between a statistical dissimilarity measure (Kullback Leibler divergence) and contingency tables. This coordination identifies the significant positive and negative correlations and enables pertinent influence rules extraction.

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来源期刊

2007 International Multi-Conference on Computing in the Global Information Technology (ICCGI'07)

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