Christianti, Devina and Abdullah, Sarini and Nurrohmah, Siti (2020) Bayes Risk Post-Pruning in Decision Tree to Overcome Overfitting Problem on Customer Churn Classification. In: Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia.
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Abstract
Classification is the process of assigning a set of data into an existing class. Decision tree is claimed to be faster and produces better accuracy compared to another classifier. However, it has some drawbacks in which the classifier is susceptible to overfitting. This problem can be avoided by pos
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 12:54 |
| Last Modified: | 17 Apr 2026 12:25 |
| URI: | http://eprints.eai.eu/id/eprint/27002 |
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