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. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Hamilton, H. J., & Karimi, K. (2005). The TIMERS II algorithm for the discovery of causality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3518 LNAI, pp. 744–750). Springer Verlag. https://doi.org/10.1007/11430919_86
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