Teaching Content Design and Organization of Data Mining Course for Statistics Postgraduates

XING XU, BING XIANG LIU, NA HU

Abstract


The data mining course is very important course for statistics postgraduates. In this paper, firstly, the theory teaching content of data mining course is introduced. It contains ten parts, that are data mining concept, the data warehouse, data pre-processing, association rules, clustering algorithm, the decision tree algorithm, the neural network, intelligent optimization algorithm, web mining, recent advances in data mining. Secondly, the experimental teaching content is introduced. It contains six experiments. Finally a teaching case is introduced. The case is about the Jingdezhen Changjiang water quality prediction which uses the neural network and intelligent optimization algorithm which are described in the theory and experiment part.

Keywords


Data mining; Teaching content design; Theory teaching; Experimental teaching; Cases teaching


DOI
10.12783/dtetr/mcee2017/15787

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