The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A k-nearest neighbor classification rule based on Dempster-Shafer theory
Abstract
In this paper, the problem of classifying an unseen pattern on the basis of its nearest neighbors in a recorded data set is addressed from the point of view of Dempster-Shafer theory. Each neighbor of a sample to be classified is considered as an item of evidence that supports certain hypotheses regarding the class membership of that pattern. The degree of support is defined as a function of the distance between the two vectors. The evidence of the k nearest neighbors is then pooled by means of Dempster's rule of combination. This approach provides a global treatment of such issues as ambiguity and distance rejection, and imperfect knowledge regarding the class membership of training patterns. The effectiveness of this classification scheme as compared to the voting and distance-weighted k-NN procedures is demonstrated using several sets of simulated and real-world data.>
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Nearest neighbor pattern classification
Cover, T., & Hart, P. (1967) · IEEE Transactions on Information Theory · doi:10.1109/tit.1967.1053964 · Cited by 16,936
A Mathematical Theory of Evidence
Shafer, G. (1976) · Princeton University Press eBooks · doi:10.1515/9780691214696 · Cited by 9,083
A fuzzy K-nearest neighbor algorithm
Keller, J. M., Gray, M. R., & Givens, J. A. (1985) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1985.6313426 · Cited by 2,648
Discriminatory analysis: Nonparametric discrimination: Consistency properties: (471672008-001)
Fix, E., & Hodges, J. L. (1951) · PsycEXTRA Dataset · doi:10.1037/e471672008-001 · Cited by 1,696
The Distance-Weighted k-Nearest-Neighbor Rule
Dudani, S. A. (1976) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1976.5408784 · Cited by 1,471
On optimum recognition error and reject tradeoff
Chow, C. (1970) · IEEE Transactions on Information Theory · doi:10.1109/tit.1970.1054406 · Cited by 929
Classification of radar returns from the ionosphere using neural networks
Sigillito, V. G. (1989) · Johns Hopkins APL technical digest · Cited by 344
Approximations for efficient computation in the theory of evidence
Tessem, B. (1993) · Artificial Intelligence · doi:10.1016/0004-3702(93)90072-j · Cited by 234
A Note on Distance-Weighted k-Nearest Neighbor Rules
(1978) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1978.4309958 · Cited by 231
The Nearest Neighbor Classification Rule with a Reject Option
Hellman, M. E. (1970) · IEEE Transactions on Systems Science and Cybernetics · doi:10.1109/tssc.1970.300339 · Cited by 218
Cited by
Brain Computer Interfaces, a Review
Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012) · Sensors · doi:10.3390/s120201211 · Cited by 2,143
Classification in the Presence of Label Noise: A Survey
Frenay, B., & Verleysen, M. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2292894 · Cited by 1,777
Some remarks on protein attribute prediction and pseudo amino acid composition
Chou, K.-C. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.12.024 · Cited by 1,225
Chou, K.-C., & Shen, H.-B. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011335 · Cited by 1,157
Recent progress in protein subcellular location prediction
Chou, K.-C., & Shen, H.-B. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.07.006 · Cited by 770
Metadata
- Authors
- Denoeux, T.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics
- Published
- 1995-05
- Volume
- 25
- Issue
- 5
- Pages
- 804-813
- ISSN
- 0018-9472 (ISSN-L)
- OpenAlex
- W2403746960
- Cited by
- 1,013
- References
- 12
- FWCI
- 8.14
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A k-nearest neighbor classification rule based on Dempster-Shafer theory. https://app.cochat.ai/papers/10.1109/21.376493
- The paper
- Denoeux, T. (1995). A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems, Man, and Cybernetics. https://doi.org/10.1109/21.376493
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.
