Integrating Association Rules with Decision Trees in Object-Relational Databases
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-3 |
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| Year of Publication : 2019 | ||
| Authors : Maruthi Rohit Ayyagari | ||
| DOI : 10.14445/22312803/IJCTT-V67I3P120 |
MLA Style: Maruthi Rohit Ayyagari, "Integrating Association Rules with Decision Trees in Object-Relational Databases" International Journal of Computer Trends and Technology 67.3 (2019): 102-108.
APA Style:Maruthi Rohit Ayyagari, (2019). Integrating Association Rules with Decision Trees in Object-Relational Databases. International Journal of Computer Trends and Technology, 67(3), 102-108.
Abstract
Research has provided evidence that associative classificationproduces more accurate results compared to other classification models. The Classification Based on Association (CBA) is one of the famous Associative Classification algorithms that generates accurate classifiers. However, current association classification algorithms reside externalto databases, which reduces the flexibility of enterprise analytics systems. Thispaper implementsthe CBA in Oracledatabase using two variant models—hardcoding the CBA in Oracle Data Mining (ODM)package and Integrating OracleApriori model with the OracleDecision tree model. We comparedthe proposed model performance with Naïve Bayes, Support Vector Machine, Random Forests, and Decision Tree over 18 datasets from UCI. Results showed that our models outperformed the original CBA model with 1% and is competitive to chosen classification models over benchmark datasets.
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Keywords
Associative Classification; Decision Trees; CBA; Oracle;Data Mining;Database