Details

Title

Visual data analysis with computational intelligence methods

Journal title

Bulletin of the Polish Academy of Sciences: Technical Sciences

Yearbook

2010

Numer

No 3 September

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences

Date

2010

Identifier

ISSN 0239-7528, eISSN 2300-1917

References

Agrawal R. (1999), Mining association rules between sets of items in large databases, null, 1, 207. ; Castillo E. (1997), Expert Systems and Probabilistic Network Models. ; Pearl J. (1993), Aspects of graphical models connected with causality, null, 1. ; Lauritzen S. (1988), Local computations with probabilities on graphical structures and their application to expert systems, J. Royal Statistical Society, B2, 50, 157. ; Pearl J. (1988), Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. ; Agrawal R. (1996), Fast discovery of association rules, Advances in Knowledge Discovery and Data Mining, 1, 307. ; Yao Y. (1999), An analysis of quantitative measures associated with rules, Methodologies for Knowledge Discovery and Data Mining, 1. ; Cooper G. (1992), A Bayesian method for the induction of probabilistic networks from data, Machine Learning, 9, 309. ; Heckerman D. (1995), Learning Bayesian networks: the combination of knowledge and statistical data, Microsoft Research, Advanced Technology Division. ; Borgelt C. (1997), Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures, null, 1, 71. ; Borgelt C. (1998), Probabilistic and possibilistic networks and how to learn them from data, Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications, 1, 403. ; Han J. (2000), Mining frequent patterns without candidate generation, null, 5, 1. ; Goethals B. (2000), On supporting interactive association rule mining, null, 1874, 307. ; Chen M.-C. (2007), Ranking discovered rules from data mining with multiple criteria by data envelopment analysis, Expert Systems with Applications, 33, 4, 1110. ; M. Müller, "Entdeckung interessanter Assoziationsregeln", <i>Master's Thesis</i>, Otto-Friedrich-Universität Bamberg & DaimlerChrysler Research and Technology, RMI/DM, Ulm, 2005. ; Steinbrecher M. (2008), Visualization of local dependencies of possibilistic network structures, Granular Computing: at the Junction of Rough Sets and Fuzzy Sets, 224, 93.

DOI

10.2478/v10175-010-0037-z

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