Association rule significance test method and device capable of considering data uncertainty

Abstract

The invention is suitable for the technical field of data mining, and provides an association rule significance test method and device capable of considering data uncertainty. The method comprises the following steps: obtaining an association rule, and judging whether the obtained association rule is an efficient rule or not; if the association rule is not the efficient rule, considering the association rule as a false rule; if the association rule is not the efficient rule, carrying out statistical test on the association rule, judging whether the value of a statistical test amount is lower than a preset significance level or not, and if the value of statistical test amount is lower than the preset significance level, accepting that the association rule is a true rule; and otherwise, considering as the association rule as the false rule. On the basis of a statistical sound test method, a family error rate can be controlled at a low level; and influence on statistical test operation by a random data error is corrected, so that the loss of the true rule in a statistical test result due to random data errors can be remarkably recovered, and the reliability of an association rule mining result is greatly improved. 本发明适用于数据挖掘技术领域，提供了顾及数据不确定性的关联规则显著性检验方法及装置。所述方法包括：获取关联规则，并判断获取的所述关联规则是否为高效规则；若所述关联规则不为所述高效规则，则认为所述关联规则为虚假规则；若所述关联规则为所述高效规则，则对所述关联规则进行统计检验，并判断所得检验统计量的值是否低于预设显著性水平，若是，则接受所述关联规则为真实规则；若否，则认为所述关联规则为虚假规则。本发明基于统计健全检验法，能将族错误率控制在较低水平；修正随机数据误差对所述统计检验运算的影响，由此显著恢复由于随机数据误差引起的统计检验结果中真实规则的丢失，大大提高了关联规则挖掘结果的可靠性。