Expert deduction rules in data mining with association rules: a case study von Rauch, Jan

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An XML Format for Association Rule Models Based on the GUHA Method von Kliegr, Tomáš, Rauch, Jan

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A novel algorithm weighting different importance of classes in enhanced association rules von Máša, Petr, Rauch, Jan

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A novel algorithm for mining couples of enhanced association rules based on the number of output couples and its application von Máša, Petr, Rauch, Jan

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Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009, Proceedings von Rauch, Jan, Ras, Zbigniew W, Berka, Petr, Elomaa, Tapio

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Apriori and GUHA – Comparing two approaches to data mining with association rules von Rauch, Jan, Šimůnek, Milan

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Logic of Association Rules von Rauch, Jan

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The GUHA method and its meaning for data mining von Hájek, Petr, Holeňa, Martin, Rauch, Jan

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Enhanced Association Rules and Python von Máša, Petr, Rauch, Jan

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Principles of data mining and knowledge discovery von Zytkow, Jan, Rauch, Jan

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Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009. Proceedings

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Special issue on data analysis methodologies for intelligent systems: guest editor’s introduction von Elomaa, Tapio, Berka, Petr, Rauch, Jan

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Detecting Temporal Trends of Technical Phrases by Using Importance Indices and Linear Regression von Abe, Hidenao, Tsumoto, Shusaku

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Domain Knowledge and Data Mining with Association Rules – A Logical Point of View von Rauch, Jan

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Data Mining with Histograms -- A Case Study von Rauch, Jan, Šimůnek, Milan

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Learning Association Rules from Data through Domain Knowledge and Automation von Rauch, Jan, Šimůnek, Milan

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Meta-learning for Post-processing of Association Rules von Berka, Petr, Rauch, Jan

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Mining and Post-processing of Association Rules in the Atherosclerosis Risk Domain von Berka, Petr, Rauch, Jan

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EverMiner Prototype Using LISp-Miner Control Language von Šimůnek, Milan, Rauch, Jan

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An OWL Ontology for Fuzzy OWL 2 von Bobillo, Fernando, Straccia, Umberto

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