The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Bump hunting in high-dimensional data
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Spline Models for Observational Data
Wahba, G. (1990) · doi:10.1137/1.9781611970128 · Cited by 4,184
Learning Logical Definitions from Relations
Quinlan, J. R. (1990) · Machine Learning · doi:10.1023/a:1022699322624 · Cited by 1,644
Cited by
Interpretable machine learning: Fundamental principles and 10 grand challenges
Rudin, C., Chen, C., Chen, Z., Huang, H., Semenova, L., & Zhong, C. (2022) · Statistics Surveys · doi:10.1214/21-ss133 · Cited by 958
Many objective robust decision making for complex environmental systems undergoing change
Kasprzyk, J. R., Nataraj, S., Reed, P. M., & Lempert, R. J. (2013) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2012.12.007 · Cited by 508
Tutorial in biostatistics: data‐driven subgroup identification and analysis in clinical trials
Lipkovich, I., Dmitrienko, A., & B., R. (2017) · Statistics in Medicine · doi:10.1002/sim.7064 · Cited by 291
Kwakkel, J. H., Haasnoot, M., & Walker, W. E. (2016) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2016.09.017 · Cited by 261
Confidence-based classifier design
Li, M., & Sethi, I. K. (2006) · Pattern Recognition · doi:10.1016/j.patcog.2006.01.010 · Cited by 61
Metadata
- Authors
- Friedman, J. H., & Fisher, N. I.
- Venue
- Statistics and Computing
- Published
- 1999-04
- Volume
- 9
- Issue
- 2
- Pages
- 123-143
- ISSN
- 0960-3174 (ISSN-L)
- 1573-1375
- OpenAlex
- W1531520279
- Cited by
- 601
- References
- 5
- FWCI
- 20.91
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Bump hunting in high-dimensional data. https://app.cochat.ai/papers/10.1023/a:1008894516817
- The paper
- Friedman, J. H., & Fisher, N. I. (1999). Bump hunting in high-dimensional data. Statistics and Computing. https://doi.org/10.1023/a%3A1008894516817
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.