Mugambi, Ernest Muthomi and Hunter, Andrew (2003) Multi-objective genetic programming optimization of decision trees for classifying medical data. In: Seventh International Conference on Knowledged-Based Intelligent Information & Engineering Systems, 3-5 September 2003, University of Oxford, UK.
Full text not available from this repository. (Request a copy)Abstract
Although there has been considerable study in the area of trading- off accuracy and comprehensibility of decision tree models, the bulk of the methods dwell on sacrificing comprehensibility for the sake of accuracy, or fine-tuning the balance between comprehensibility and accuracy. Invariably, the level of trade-off is decided {tshape a priori}. It is possible for such decisions to be made {tshape a posteriori} which means the induction process does not discriminate against any of the objectives. In this paper, we present such a method that uses multi-objective Genetic Programming to optimize decision tree models. We have used this method to build decision tree models from Diabetes data in a bid to investigate its capability to trade-off comprehensibility and performance.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Although there has been considerable study in the area of trading- off accuracy and comprehensibility of decision tree models, the bulk of the methods dwell on sacrificing comprehensibility for the sake of accuracy, or fine-tuning the balance between comprehensibility and accuracy. Invariably, the level of trade-off is decided {tshape a priori}. It is possible for such decisions to be made {tshape a posteriori} which means the induction process does not discriminate against any of the objectives. In this paper, we present such a method that uses multi-objective Genetic Programming to optimize decision tree models. We have used this method to build decision tree models from Diabetes data in a bid to investigate its capability to trade-off comprehensibility and performance. |
| Keywords: | decision trees, multi-objective genetic programming, classifying medical data, optimize decision tree |
| Subjects: | G Mathematical and Computer Sciences > G400 Computer Science |
| Divisions: | College of Sciences > Faculty of Science > Lincoln School of Computer Science |
| Depositing User: | Rosaline Smith |
| Date Deposited: | 09 Jul 2010 13:36 |
| Last Modified: | 30 Apr 2013 08:54 |
| URI: | http://eprints.lincoln.ac.uk/id/eprint/2827 |
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