Preprocessing for Data Mining and Decision Support
The goal of this chapter is to identify data preprocessing tasks that can benefit from the existence of software support, and to describe the basic requirements on the tool, which can serve this purpose. These requirements are implemented in the data transformation tool, SumatraTT. The design principles and basic functionality of SumatraTT are explained. The chapter concludes by a brief evaluation of experience gained using SumatraTT was in different tasks, and with a summary of plans for its further development.
KeywordsData Mining Data Transformation Data Preparation Data Mining Algorithm Data Mining Process
Unable to display preview. Download preview PDF.
- Aubrecht, P. and Kouba, Z. (2001). Meta-Data Driven Data Transformation. Proc. 5th World Muti-conference on Systemics, Cybernetics and Informatics.Google Scholar
- Kietz, J. U., Vaduva, A. and Zücker, R. (2001). MiningMart: Metadata-Driven Preprocessing. Proc. ECMUPKDD Workshop on Database Support for KDD.Google Scholar
- MiningMart (2003). MiningMart project:, http://www-ai.cs.uni-dortund.de/MMWEB/research/index.html
- Morik, K. and Scholz, M. (2003). The MiningMart Approach to Knowledge Discovery in Databases, In (eds. Zhong, N. and Liu, J.), Handbook of Intelligent IT, IOS Press.Google Scholar
- Pyle, D. (1999), Data Preparation for Data Mining, Morgan Kaufmann.Google Scholar
- SumatraTT (2003). available at, http://krizik.felk.cvut.cz/Sumatra/Sumatra
- Zücker, R. and Kietz, J.-U. (2000). How to preprocess large databases, In Proc. PKDD 2000 Workshop on Data Mining, Decision Support, Meta-learning and ILP: Forum for Practical Problem Presentation and Prospective Solutions, (eds. Brazdil P., Jorge A.), University of Porto.Google Scholar