Knowledge Discovery from Database Using an Integration of Clustering and Association Rule Mining

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Data mining is the process of automatic classification of cases based on data patterns obtained from a dataset. a number of algorithms have been developed and implemented to extract information and discover knowledge patterns that may be useful for decision support. Clustering and association are two important techniques of data mining. Association rule learning is a well researched method for discovering interesting relations between variables in large databases. It identifies and defines strong rules discovered in databases using different measures of interestingness. While, clustering is an unsupervised learning problem that group objects based upon distance or similarity.

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