Hybrid Pruning Algorithm
| Autor: | Du Xiangran, Wan Yuanyuan, Wang Xizhao |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Weighted Majority Algorithm
Computer science business.industry Population-based incremental learning Decision tree ID3 algorithm Machine learning computer.software_genre Principal variation search Null-move heuristic Pruning (decision trees) Artificial intelligence business computer Algorithm Killer heuristic |
| Zdroj: | 2009 International Forum on Computer Science-Technology and Applications. |
| DOI: | 10.1109/ifcsta.2009.13 |
| Popis: | In this paper we develop a new post-pruning algorithm. This new pruning algorithm uses two or more post-pruning algorithms to prune a decision tree that has been built on training set by different orders, and the “best” tree is selected based either on separate test set accuracy or cross-validations from trees coming from result of the above step. The algorithm is theoretically based on occam's razor that is a simpler model is chosen if two models have the same performance on the training set. An experiment is implemented on three databases in UCI machine learning repository and the new algorithm is employed to compares with two well-known post-pruning algorithms. The results show that the hybrid pruning algorithm effectively reduces the complexity of decision trees without sacrificing accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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