The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Least squares twin support vector machines for pattern classification
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Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
A Tutorial on Support Vector Machines for Pattern Recognition
Burges, C. J. C. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009715923555 · Cited by 16,429
Least Squares Support Vector Machine Classifiers
Suykens, J. A. K., & Vandewalle, J. (1999) · Neural Processing Letters · doi:10.1023/a:1018628609742 · Cited by 9,362
An algorithm for suffix stripping
Porter, M. F. (1980) · Program · doi:10.1108/eb046814 · Cited by 8,096
Text categorization with Support Vector Machines: Learning with many relevant features
Joachims, T. (1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0026683 · Cited by 7,999
A TUTORIAL ON SUPPORT VECTOR MACHINES FOR PATTERN RECOGNITION, DATA MINING AND KNOWLEDGE DISCOVERY
Burger, C. J. C. (1998) · Cited by 3,247
Mangasarian, O. L. (1994) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971255 · Cited by 3,220
Twin Support Vector Machines for Pattern Classification
Jayadeva, Khemchandani, R., & Chandra, S. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1068 · Cited by 1,803
Inductive learning algorithms and representations for text categorization
Dumais, S., Platt, J., Heckerman, D., & Sahami, M. (1998) · Proceedings of the seventh international conference on Information and knowledge management · doi:10.1145/288627.288651 · Cited by 1,461
Proximal support vector machine classifiers
Fung, G., & Mangasarian, O. L. (2001) · Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/502512.502527 · Cited by 842
Cited by
A novel cryptocurrency price trend forecasting model based on LightGBM
Sun, X., Liu, M., & Sima, Z. (2020) · Finance Research Letters · doi:10.1016/j.frl.2018.12.032 · Cited by 519
Nonparallel Support Vector Machines for Pattern Classification
Tian, Y., Qi, Z., Ju, X., Shi, Y., & Liu, X. (2014) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2013.2279167 · Cited by 261
Multi-class Classification Methods of Enhanced LS-TWSVM for Strip Steel Surface Defects
Chu, M.-X., Wang, A.-N., Gong, R.-F., & Sha, M. (2014) · Journal of Iron and Steel Research International · doi:10.1016/s1006-706x(14)60027-3 · Cited by 21
Metadata
- Authors
- Arun Kumar, M., & Gopal, M.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2009-05
- Volume
- 36
- Issue
- 4
- Pages
- 7535-7543
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2019184604
- Cited by
- 639
- References
- 12
- FWCI
- 19.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- Arun Kumar, M., & Gopal, M. (2009). Least squares twin support vector machines for pattern classification. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2008.09.066
Data sources
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.
