文章基本信息

标题：Generation and Interpretation of Temporal Decision Rules
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作者：Kamran Karimi ; Howard J. Hamilton
期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2011
卷号：3
页码：314-323
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：We present a solution to the problem of understanding a system that produces a sequence of temporally ordered observations. Our solution is based on generating and interpreting a set of temporal decision rules. A temporal decision rule is a decision rule that can be used to predict or retrodict the value of a decision attribute, using condition attributes that are observed at times other than the decision attribute's time of observation. A rule set, consisting of a set of temporal decision rules with the same decision attribute, can be interpreted by our Temporal Investigation Method for Enregistered Record Sequences (TIMERS) to signify an instantaneous, an acausal or a possibly causal relationship between the condition attributes and the decision attribute. We show the effectiveness of our method, by describing a number of experiments with both synthetic and real temporal data.
关键词：Data Mining; Decision Rule Discovery; Causality; ; Acausality; Temporal Rules