The TIMERS II algorithm for the discovery of causality

Authors:
Howard J. Hamilton;Kamran Karimi
Affiliations:
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Venue:
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Year:
2005

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Abstract

We present the Temporal Investigation Method for Enregistered Record Sequences II (TIMERS II), which can be used to classify the relationship between a decision attribute and a number of condition attributes as instantaneous, causal, or acausal. In this paper we consider it possible to refer to both previous and next values of attributes in temporal rules, and thus enhance the definition of acausality. We also present a new algorithm for distinguishing between causality and acausality.