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

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書目名稱Association Rule Mining影響因子(影響力)




書目名稱Association Rule Mining影響因子(影響力)學(xué)科排名




書目名稱Association Rule Mining網(wǎng)絡(luò)公開度




書目名稱Association Rule Mining網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Association Rule Mining被引頻次




書目名稱Association Rule Mining被引頻次學(xué)科排名




書目名稱Association Rule Mining年度引用




書目名稱Association Rule Mining年度引用學(xué)科排名




書目名稱Association Rule Mining讀者反饋




書目名稱Association Rule Mining讀者反饋學(xué)科排名

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Causality in Databases,cepts are defined in Section 4.2. In Section 4.3 we first define a ‘good partition’ for generating item variables from items, and we then present a method of mining causality of interest from large databases. In Section 4.4 we advocate an approach for finding dependencies among variables. In Section

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/163505.jpg

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978-3-540-43533-4Springer-Verlag Berlin Heidelberg 2002

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étienne André,Didier Lime,Mathias Ramparisonation rule mining in this chapter, we will concentrate on introducing data mining techniques..In Section 1.1 we begin with explaining what data mining is. In Section 1.2 we argue as to why data mining is needed. In Section 1.3 we recall the process of knowledge discovery in databases (KDD). In Secti

annexation

Lecture Notes in Computer Sciencesearch into the improvement of association rule mining techniques is also introduced to clarify the process. The chapter is organized as follows. In Section 2.1, we begin by outlining certain necessary basic concepts. Some measurements of association rules are discussed in Section 2.2. In Section 2.

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