The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
A comparative evaluation of outlier detection algorithms: Experiments and analyses
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Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
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UCI Machine Learning Repository
Asuncion, A. (2007) · Medical Entomology and Zoology · Cited by 24,156
Liu, F. T., Ting, K. M., & Zhou, Z.-H. (2008) · 2008 Eighth IEEE International Conference on Data Mining · doi:10.1109/icdm.2008.17 · Cited by 6,601
The relationship between Precision-Recall and ROC curves
Davis, J., & Goadrich, M. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143874 · Cited by 6,559
LOF: identifying density-based local outliers
Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335388 · Cited by 5,207
Probabilistic Principal Component Analysis
Tipping, M. E., & Bishop, C. M. (1999) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00196 · Cited by 3,679
A Survey of Outlier Detection Methodologies
Hodge, V., & Austin, J. (2004) · Artificial Intelligence Review · doi:10.1007/s10462-004-4304-y · Cited by 3,596
The class imbalance problem: A systematic study1
Japkowicz, N., & Stephen, S. (2002) · Intelligent Data Analysis · doi:10.3233/ida-2002-6504 · Cited by 3,295
Advances in neural information processing systems 11
Peter Sollich, A. (1999) · Cited by 3,168
Multivariate Density Estimation, Theory, Practice, and Visualbation
Ramsay, P. H. (1993) · Technometrics · doi:10.1080/00401706.1993.10485361 · Cited by 2,789
Cited by
Using machine learning approaches for multi-omics data analysis: A review
Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903
Progress in Outlier Detection Techniques: A Survey
Wang, H., Bah, M. J., & Hammad, M. (2019) · IEEE Access · doi:10.1109/access.2019.2932769 · Cited by 523
Big data analysis for brain tumor detection: Deep convolutional neural networks
Amin, J., Sharif, M., Yasmin, M., & Fernandes, S. L. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.04.065 · Cited by 327
Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data
Xi, N. M., & Li, J. J. (2021) · Cell Systems · doi:10.1016/j.cels.2020.11.008 · Cited by 208
Machine learning based approach to exam cheating detection
Kamalov, F., Sulieman, H., & Santandreu Calonge, D. (2021) · PLOS ONE · doi:10.1371/journal.pone.0254340 · Cited by 102
Metadata
- Authors
- Domingues, R., Filippone, M., Michiardi, P., & Zouaoui, J.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 74
- Pages
- 406-421
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2760451156
- Cited by
- 452
- References
- 36
- FWCI
- 24.11
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Domingues, R., Filippone, M., Michiardi, P., & Zouaoui, J. (2018). A comparative evaluation of outlier detection algorithms: Experiments and analyses. Pattern Recognition. https://doi.org/10.1016/j.patcog.2017.09.037
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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.
