Szczegóły Szczegóły PDF BIBTEX RIS Tytuł artykułu Visual data analysis with computational intelligence methods Tytuł czasopisma Bulletin of the Polish Academy of Sciences Technical Sciences Rocznik 2010 Wolumin 58 Numer No 3 Autorzy Kruse, R. ; Steinbrecher, M. Wydział PAN Nauki Techniczne Zakres 393-401 Data 2010 Identyfikator DOI: 10.2478/v10175-010-0037-z ; ISSN 2300-1917 Źródło Bulletin of the Polish Academy of Sciences: Technical Sciences; 2010; 58; No 3; 393-401 Referencje 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.