The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks
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UCI Machine Learning Repository
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Classification and regression trees
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A detailed analysis of the KDD CUP 99 data set
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A survey of decision tree classifier methodology
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Cited by
A review of clustering techniques and developments
Saxena, A., Prasad, M., Gupta, A., Bharill, N., Patel, O. P., Tiwari, A., Er, M. J., Ding, W., & Lin, C.-T. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.06.053 · Cited by 1,357
Advancing Biosensors with Machine Learning
Cui, F., Yue, Y., Zhang, Y., Zhang, Z., & Zhou, H. S. (2020) · ACS Sensors · doi:10.1021/acssensors.0c01424 · Cited by 768
A deep learning method with wrapper based feature extraction for wireless intrusion detection system
Kasongo, S. M., & Sun, Y. (2020) · Computers & Security · doi:10.1016/j.cose.2020.101752 · Cited by 373
A machine learning based robust prediction model for real-life mobile phone data
Sarker, I. H. (2019) · Internet of Things · doi:10.1016/j.iot.2019.01.007 · Cited by 113
Ryu, H., Kim, S., Kim, D., Han, S., Lee, K., & Kang, Y. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3415223 · Cited by 66
Metadata
- Authors
- Farid, D. M., Zhang, L., Rahman, C. M., Hossain, M. A., & Strachan, R.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2014-03
- Volume
- 41
- Issue
- 4
- Pages
- 1937-1946
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2032477387
- Cited by
- 368
- References
- 28
- FWCI
- 58.48
- Type
- journal article
- Language
- en
- Open access
- closed
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- Farid, D. M., Zhang, L., Rahman, C. M., Hossain, M. A., & Strachan, R. (2014). Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2013.08.089
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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.
