Abstract
The emerging standard for the platform- and system-independent representation of data mining models, PMML (Predictive Model Markup Language), is currently supported by a number of knowledge discovery support engines (KDDSE). The primary purpose of the PMML standard is to separate model generation from model storage in order to enable users to view, post-process, and utilize data mining models independently of the KDDSE that generated the model. In this chapter, an architectural framework for collaborative data mining and decision support that utilizes PMML is described. Important parts of such a general framework are visualization and evaluation methods for data mining models. Two such systems, called VizWiz and PEAR, are described in some detail.
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Wettschereck, D., Jorge, A., Moyle, S. (2003). Data Mining and Decision Support Integration through the Predictive Model Markup Language Standard and Visualization. In: Mladenić, D., Lavrač, N., Bohanec, M., Moyle, S. (eds) Data Mining and Decision Support. The Springer International Series in Engineering and Computer Science, vol 745. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0286-9_10
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DOI: https://doi.org/10.1007/978-1-4615-0286-9_10
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