The TIMERS II algorithm for the discovery of causality

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3518 LNAI, Issue , 2005, Pages 744-750

  Hamilton, Howard J ^a   Karimi, Kamran ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; DECISION THEORY; KNOWLEDGE BASED SYSTEMS;

DECISION ATTRIBUTE; ENREGISTERED RECORD SEQUENCES; TEMPORAL INVESTIGATION METHOD;

DATA MINING;

EID: 26944446931     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11430919_86     Document Type: Conference Paper

References (5)

1. Karimi, K., and Hamilton, H.J. TimeSleuth: A Tool for Discovering Causal and Temporal Rules, The 14th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2002), Washington DC, November, 2002, pp. 375-380.
2. Karimi, K., and Hamilton, H.J., Distinguishing Causal and Acausal Temporal Relations, The Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2003), Seoul, South Korea, April/May 2003, pp. 234-240.
3. Karimi, K., and Hamilton, H.J., An Extension to the TIMERS Method, Technical Report CS-2005-02, Department of Computer Science, University of Regina, Canada, March 2005.
4. Witten, I.A., and Frank, E., Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann, 2000.
5. http://typhoon.bae.lsu.edu/datatabl/current/sugcurrh.html. Contents change with time.