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Improved Use of Continuous Attributes in C4.5
Open accessAbstract
A reported weakness of C4.5 in domains with continuous attributes is addressed by modifying the formation and evaluation of tests on continuous attributes. An MDL-inspired penalty is applied to such tests, eliminating some of them from consideration and altering the relative desirability of all tests. Empirical trials show that the modifications lead to smaller decision trees with higher predictive accuracies. Results also confirm that a new version of C4.5 incorporating these changes is superior to recent approaches that use global discretization and that construct small trees with multi-interval splits.
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Cites
A decision-theoretic generalization of on-line learning and an application to boosting
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Data Mining: Practical Machine Learning Tools and Techniques
(2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,437
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Murthy, S. K. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009744630224 · Cited by 991
LightFace: A Hybrid Deep Face Recognition Framework
Serengil, S. I., & Ozpinar, A. (2020) · 2020 Innovations in Intelligent Systems and Applications Conference (ASYU) · doi:10.1109/asyu50717.2020.9259802 · Cited by 347
Simplifying decision trees: A survey
BRESLOW, L. A., & AHA, D. W. (1997) · The Knowledge Engineering Review · doi:10.1017/s0269888997000015 · Cited by 337
A Pearson’s correlation coefficient based decision tree and its parallel implementation
Mu, Y., Liu, X., & Wang, L. (2018) · Information Sciences · doi:10.1016/j.ins.2017.12.059 · Cited by 336
Metadata
- Authors
- Quinlan, J. R.
- Venue
- Journal of Artificial Intelligence Research
- Publisher
- AI Access Foundation
- Published
- 1996-03-01
- Volume
- 4
- Pages
- 77-90
- ISSN
- 1076-9757 (ISSN-L)
- OpenAlex
- W1833977909
- Cited by
- 1,846
- References
- 2
- FWCI
- 59.19
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Quinlan, J. R. (1996). Improved Use of Continuous Attributes in C4.5. Journal of Artificial Intelligence Research. https://doi.org/10.1613/jair.279
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