The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Global discretization of continuous attributes as preprocessing for machine learning
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Cites
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Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,522
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Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 20,825
Pawlak, Z. (1982) · International Journal of Computer & Information Sciences · doi:10.1007/bf01001956 · Cited by 12,322
Everitt, B. J., Landau, S., & Leese, M. (1974) · Cited by 9,168
Knowledge discovery in databases
FrawleyWilliam, J., Piatetsky-ShapiroGregory, & MatheusChristopher, J. (1992) · AI Magazine · doi:10.5555/140629.140633 · Cited by 1,055
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Intelligent decision support. Handbook of applications and advances of the rough sets theory
(1993) · Fuzzy Sets and Systems · doi:10.1016/0165-0114(93)90040-o · Cited by 803
On the handling of continuous-valued attributes in decision tree generation
Fayyad, U. M., & Irani, K. B. (1992) · Machine Learning · doi:10.1007/bf00994007 · Cited by 745
LERS-A System for Learning from Examples Based on Rough Sets
Grzymala-Busse, J. W. (1992) · Intelligent Decision Support · doi:10.1007/978-94-015-7975-9_1 · Cited by 653
Self-citation
Cited by
Pawlak, Z., & Skowron, A. (2007) · Information Sciences · doi:10.1016/j.ins.2006.06.003 · Cited by 2,070
Discretization: An Enabling Technique
Liu, H., Hussain, F., Tan, C. L., & Dash, M. (2002) · Data Mining and Knowledge Discovery · doi:10.1023/a:1016304305535 · Cited by 981
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning
Garcia, S., Luengo, J., Sáez, J. A., López, V., & Herrera, F. (2013) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2012.35 · Cited by 548
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Hu, Q., Yu, D., & Xie, Z. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.09.004 · Cited by 462
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Halim, S. M., Khan, L., & Thuraisingham, B. (2020) · 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI) · doi:10.1109/cogmi50398.2020.00038 · Cited by 16
Metadata
- Authors
- Chmielewski, M. R., & Grzymala-Busse, J. W.
- Venue
- International Journal of Approximate Reasoning
- Publisher
- Elsevier BV
- Published
- 1996-11
- Volume
- 15
- Issue
- 4
- Pages
- 319-331
- ISSN
- 0888-613X (ISSN-L)
- OpenAlex
- W2082131185
- Cited by
- 347
- References
- 13
- FWCI
- 13.40
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Chmielewski, M. R., & Grzymala-Busse, J. W. (1996). Global discretization of continuous attributes as preprocessing for machine learning. International Journal of Approximate Reasoning. https://doi.org/10.1016/s0888-613x(96)00074-6
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
