Re-mining is a general framework which suggests the execution of additional data mining steps based on the results of an original data mining process. This study investigates the multi-faceted re-mining of association mining results, develops and presents a practical methodology, and shows the applicability of the developed methodology through real world data. The methodology suggests re-mining using data visualization, data envelopment analysis, and decision trees. Six hypotheses, regarding how re-mining can be carried out on association mining results, are answered in the case study through empirical analysis.
Ertek, G., Tunç, M.M., (2012) “Re-Mining Association Mining Results through Visualization, Data Envelopment Analysis, and Decision Trees”, in Computational Intelligence Applications in Industrial Engineering, Ed: C. Kahraman, Springer.
Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.
Dr. Gürdal Ertek recommends the following related books:
- Information Visualization: Design for Interaction (2nd Edition)
- Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition
- Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition
- Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition