Titlebook: Association Rule Mining; Models and Algorithm Chengqi Zhang,Shichao Zhang Textbook 2002 Springer-Verlag Berlin Heidelberg 2002 Algorithmic

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Causal Rule Analysis,onstructing polynomial functions for approximate causality in data are advocated. Finally, we propose an approach for finding the approximate polynomial causal- ity between two variables from a given data set by fitting.

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inventory

Introduction,on 1.4 we demonstrate data mining tasks and faced data types. Section 1.5 introduces some basic data mining techniques. Section 1.6 presents data mining and marketing. In Section 1.7, we show some examples where data mining is applied to real-world problems. And, finally in Section 1.8 we discuss future work involving data mining.

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Negative Association Rule,re are essential differences between positive and negative association rule mining. Using a pruning algo- rithm we can reduce the search space, however, some pruned itemsets may be useful in the extraction of negative rules.

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Textbook 2002esearchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

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Postscript,ther it would really be different this time. While these were heard the dominant mood of participants was nevertheless one of hopeful, if measured, caution, which allowed the majority of participants to look to the future in Haiti with some optimism.

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