Patterns of multirelational data transformation in data mining process

Marcin Mazurek

Abstract


Multirelational data mining requires complex preprocessing of data. Identification of transformation patterns and implementation of reusable components lead to more robust data-mining flow construction process. In this paper concept of implementation of selected transformation patterns is presented. Rapid Miner envi-ronment is used to build transformations, which can be later used in predicting cus-tomer behavior.

Keywords


multirelational data mining; time series; propositionalization

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References


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DOI: http://dx.doi.org/10.21936/si2012_v33.n2A.168