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

Provided by: Universiti Malaysia Perlis
Topic: Data Management
Format: PDF
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.

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