Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-Based Clustering Technique

In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, the authors may loss some information when, they join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and the classification result is often not very promising especially when the number of tables and the degree of one-to-many association are large.

Provided by: Universiti Malaysia Perlis Topic: Data Management Date Added: Aug 2007 Format: PDF

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