boolean association rules

基本解释

Discovering association rules is an important data mining problem. While discovering Quantitative Association Rules differs from traditional Boolean Association Rules.
关联规则的发现是数据挖掘的一个重要方面，而数量关联规则的发现不同于传统的布尔型关联规则。
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Most quantitative association rules transform mining association rules of numeric property into boolean property, and the kernel problem is to divide the numeric data into intervals.
数值型关联规则的算法大多是将多值属性关联规则挖掘问题转化为布尔型关联规则挖掘问题，而连续属性的离散化是数值型关联规则的核心问题。
In Chapter 3, the effective Adaptive-Support Boolean algorithm for mining association rules is presented, including the Adaptive-Support frame of the algorithm and its Boolean fundamentals.
第三章提出了一种基于自适应支持度的布尔式关联规则挖掘算法，包括布尔式挖掘原理及挖掘算法的自适应支持度框架。

布尔关联规则
It is proved that every WRR can induce a Boolean association rules as its support rule.4.
证明了任意一个弱比例规则都可诱导出一个布尔关联规则作为其支撑规则。