A Simple Approach to Ordinal Classification
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Cites
Data Mining: Practical Machine Learning Tools and Techniques
Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,493 · see citing works
Self-citation(1992) · Cited by 23,431 · see citing works
Witten, I. H., & Frank, E. (2002) · ACM SIGMOD Record · doi:10.1145/507338.507355 · Cited by 5,163 · see citing works
Self-citationSolving Multiclass Learning Problems via Error-Correcting Output Codes
Dietterich, T. G., & Bakiri, G. (1995) · Journal of Artificial Intelligence Research · doi:10.1613/jair.105 · Cited by 2,698 · see citing works
Wrappers for Performance Enhancements and Oblivious Decision Graphs.
Kohavi, R. (1995) · Cited by 253 · see citing works
Prediction of Ordinal Classes Using Regression Trees
Krämer, S., Widmer, G., Pfahringer, B., & de Groeve, M. (2000) · Lecture notes in computer science · doi:10.1007/3-540-39963-1_45 · Cited by 125 · see citing works
Decision trees for ordinal classification
Potharst, R., & Bioch, J. C. (2000) · Intelligent Data Analysis · doi:10.3233/ida-2000-4202 · Cited by 87 · see citing works
Making Better Use of Global Discretization
Frank, E., & Witten, I. H. (1999) · Research Commons (University of Waikato) · Cited by 49 · see citing works
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Research works printed but not linked: 2
- [3]3. Morgan Kaufmann.
- [9]9. Morgan Kaufmann, San Fran- cisco, 1993.
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Deep Ordinal Regression Network for Monocular Depth Estimation
Fu, H., Gong, M., Wang, C., Batmanghelich, K., & Tao, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00214 · Cited by 1,991 · see citing works
Fact Checking: Task definition and dataset construction
Vlachos, A., & Riedel, S. (2014) · Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science · doi:10.3115/v1/w14-2508 · Cited by 402 · see citing works
The Effects of Twitter Sentiment on Stock Price Returns
Ranco, G., Aleksovski, D., Caldarelli, G., Grčar, M., & Mozetič, I. (2015) · PLoS ONE · doi:10.1371/journal.pone.0138441 · Cited by 395 · see citing works
“We implemented the wrapper approach, described in [46], which constructs two linearkernel SVM [42] classifiers.”
MethodDebunking in a world of tribes
Zollo, F., Bessi, A., Del Vicario, M., Scala, A., Caldarelli, G., Shekhtman, L., Havlin, S., & Quattrociocchi, W. (2017) · PLOS ONE · doi:10.1371/journal.pone.0181821 · Cited by 345 · see citing works
Emotional Dynamics in the Age of Misinformation
Zollo, F., Novak, P. K., Del Vicario, M., Bessi, A., Mozetič, I., Scala, A., Caldarelli, G., & Quattrociocchi, W. (2015) · PLOS ONE · doi:10.1371/journal.pone.0138740 · Cited by 273 · see citing works
A survey of machine learning techniques for food sales prediction
Tsoumakas, G. (2019) · Artificial Intelligence Review · doi:10.1007/s10462-018-9637-z · Cited by 134 · see citing works
Learning to assess the quality of stroke rehabilitation exercises
Lee, M. H., Siewiorek, D. P., Smailagic, A., Bernardino, A., & Badia, S. B. I. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces · doi:10.1145/3301275.3302273 · Cited by 71 · see citing works
- Authors
- Frank, E., & Hall, M.
- Affiliations
- University of Waikato (NZ)
- ORCID
- Frank, Eibe
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2001
- Pages
- 145-156
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W1997855593
- Cited by
- 606
- References
- 8
- Citations by year
- 2026: 27 · 2025: 29 · 2024: 24 · 2023: 30 · 2022: 53 · 2021: 67 · 2020: 40 · 2019: 39 · 2018: 36 · 2017: 24 · 2016: 22 · 2015: 27 · 2014: 25 · 2013: 23 · 2012: 25
- FWCI
- 2.90
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Lecture notes in computer science (publishedVersion)
- Research Commons (University of Waikato) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Keywords
- ordinal classification, decision tree, regression-based classification, post-processing
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