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  • 标题:Generation and Interpretation of Temporal Decision Rules
  • 本地全文:下载
  • 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
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