The DOI matches its Crossref record.
Covariance matrix estimation and classification with limited training data
Abstract
A new covariance matrix estimator useful for designing classifiers with limited training data is developed. In experiments, this estimator achieved higher classification accuracy than the sample covariance matrix and common covariance matrix estimates. In about half of the experiments, it achieved higher accuracy than regularized discriminant analysis, but required much less computation.
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Cited by
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Bhaskar, H., Hoyle, D. C., & Singh, S. (2006) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2005.09.002 · Cited by 109
An automatic assessment scheme for steel quality inspection
Wiltschi, K., Pinz, A., & Lindeberg, T. (2000) · Machine Vision and Applications · doi:10.1007/s001380050130 · Cited by 89
Fast probabilistic whitening transformation for ultra-high dimensional genetic data
Hoffman, G. E., Dillard, C. P., Girdhar, K., & Roussos, P. (2026) · PLOS Genetics · doi:10.1371/journal.pgen.1012320
Metadata
- Authors
- Hoffbeck, J. P., & Landgrebe, D. A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1996-07
- Volume
- 18
- Issue
- 7
- Pages
- 763-767
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2136809053
- Cited by
- 307
- References
- 0
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- closed
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Covariance matrix estimation and classification with limited training data. https://app.cochat.ai/papers/10.1109/34.506799
- The paper
- Hoffbeck, J. P., & Landgrebe, D. A. (1996). Covariance matrix estimation and classification with limited training data. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.506799
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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.
