The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A Probabilistic Theory of Pattern Recognition
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“To train the PFC classification unit in the model, we used a random splits procedure, which has been shown to provide a good estimate of the expected error of a classifier (56).”
From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [56]
In the citing paper
“It is clearly not, in general, a consistent estimate (Devroye et al., 1996, Chapter 5).”
From A random forest guided tour (2016) · cites this paper as Devroye et al. (1996)
Citations
Cites
An introduction to probability theory and its applications
(1958) · Journal of the Franklin Institute · doi:10.1016/0016-0032(58)90688-4 · Cited by 29,621
Loève, M. (1963) · Andalas University Repository (Andalas University) · Cited by 5,938
Probability: Theory and Examples.
Prewitt, K., & Durrett, R. T. (1992) · Journal of the American Statistical Association · doi:10.2307/2290301 · Cited by 3,238
Probability and Random Processes
Grimmett, G., & Stirzaker, D. (2004) · Elsevier eBooks · doi:10.1016/b978-0-12-172651-5.x5000-3 · Cited by 2,607
Probability Theory: Independence, Interchangeability, Martingales
Lund, R., Chow, Y. S., & Teicher, H. (1998) · Journal of the American Statistical Association · doi:10.2307/2670078 · Cited by 1,095
Real Analysis and Probability.
Ross, K. A., & ASH, R. B. (1975) · American Mathematical Monthly · doi:10.2307/2319153 · Cited by 727
Cited by
Sorted by citations
Data Mining: Practical Machine Learning Tools and Techniques
Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,543
A Tutorial on Support Vector Machines for Pattern Recognition
Burges, C. J. C. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009715923555 · Cited by 16,616
A tutorial on support vector regression
Smola, A. J., & Schölkopf, B. (2004) · Statistics and Computing · doi:10.1023/b:stco.0000035301.49549.88 · Cited by 13,723
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Statistical pattern recognition: a review
Jain, A. K., Duin, P., & Mao, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824819 · Cited by 6,898
Metadata
- Authors
- Devroye, L., Györfi, L., & Lugosi, G.
- Affiliations
- McGill University (CA)
- Budapest University of Technology and Economics (HU)
- Venue
- Stochastic Modelling and Applied Probability
- Publisher
- Springer New York
- Published
- 1996
- ISSN
- 2197-4381 (ISSN-L)
- 0172-4568
- 2197-439X
- OpenAlex
- W1564947197
- Cited by
- 3,274
- References
- 6
- Citations by year
- 2026: 31 · 2025: 57 · 2024: 74 · 2023: 69 · 2022: 101 · 2021: 113 · 2020: 131 · 2019: 136 · 2018: 106 · 2017: 98 · 2016: 120 · 2015: 150 · 2014: 125 · 2013: 119 · 2012: 141
- FWCI
- 20.89
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Stochastic modelling and applied probability (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- distance measures, kernel methods, nearest neighbors, Vapnik-Chervonenkis theory, epsilon-entropy, parametric classification, error estimation, classification trees, artificial neural networks
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.
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