Algebraic aspects of attribute dependencies in information systems
Fundamenta Informaticae
Predictive data mining: a practical guide
Predictive data mining: a practical guide
Principles of Database Systems
Principles of Database Systems
Data Mining and Knowledge Discovery
Data Ranking Based on Spatial Partitioning
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
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The function of data reduction is to make data sets smaller, while preserving classification structures of interest. A novel approach to data reduction based on spatial partitioning is proposed in this paper. This algorithm projects conventional database relations into multidimensional data space. The advantage of this approach is to change the data reduction process into a spatial merging process of data in the same class, as well as a spatial partitioning process of data in different classes, in multidimensional data space. A series of partitioned regions are eventually obtained and can easily be used in data classification. The proposed method was evaluated using 7 real world data sets. The results were quite remarkable compared with those obtained by C4.5 and DR. The efficiency of the proposed algorithm was better than DR without loss of test accuracy and reduction ratio.