The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Discriminant adaptive nearest neighbor classification
Abstract
Nearest neighbour classification expects the class conditional probabilities to be locally constant, and suffers from bias in high dimensions. We propose a locally adaptive form of nearest neighbour classification to try to ameliorate this curse of dimensionality. We use a local linear discriminant analysis to estimate an effective metric for computing neighbourhoods. We determine the local decision boundaries from centroid information, and then shrink neighbourhoods in directions orthogonal to these local decision boundaries, and elongate them parallel to the boundaries. Thereafter, any neighbourhood-based classifier can be employed, using the modified neighbourhoods. The posterior probabilities tend to be more homogeneous in the modified neighbourhoods. We also propose a method for global dimension reduction, that combines local dimension information. In a number of examples, the methods demonstrate the potential for substantial improvements over nearest neighbour classification.
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Cites
Nearest neighbor pattern classification
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McLachlan, G. J. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/0471725293 · Cited by 1,267
Penalized Discriminant Analysis
Hastie, T., Buja, A., & Tibshirani, R. (1995) · The Annals of Statistics · doi:10.1214/aos/1176324456 · Cited by 849
Self-citationNeural Networks and Related Methods for Classification
Ripley, B. D. (1994) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1994.tb01990.x · Cited by 627
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Slicing Regression: A Link-Free Regression Method
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Similarity Metric Learning for a Variable-Kernel Classifier
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Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., et al. (2008) · Knowledge and Information Systems · doi:10.1007/s10115-007-0114-2 · Cited by 5,667
Approximate nearest neighbors: towards removing the curse of dimensionality
Indyk, P., & Motwani, R. (1998) · Proceedings of the thirtieth annual ACM symposium on Theory of computing - STOC '98 · doi:10.1145/276698.276876 · Cited by 4,188
(1999) · Cited by 3,186
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
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
Zhang, H., Berg, A. C., Maire, M., & Malik, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.301 · Cited by 1,114
Metadata
- Authors
- Hastie, T., & Tibshirani, R.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1996-06
- Volume
- 18
- Issue
- 6
- Pages
- 607-616
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W1545745930
- Cited by
- 833
- References
- 12
- FWCI
- 16.23
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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