Probabilistic D-Clustering
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David Bau and Jun-Yan Zhu present an analytical framework to visualize and comprehend GANs at the unit, object, and scene levels.
“David Bau and Jun-Yan Zhu present an analytical framework [43] to visualize and comprehend GANs at the unit, object, and scene levels.”
From Comparative Analysis of Intrusion Detection Systems and Machine Learning Based Model Analysis through Decision Tree (2023) · cites this paper as [43]
Cites
Pattern Recognition with Fuzzy Objective Function Algorithms
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Algorithms for Clustering Data
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Another proof of the defect relation for moving targets
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Harmonic Mean Measure of Animal Activity Areas
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A Unified Continuous Optimization Framework for Center-Based Clustering Methods
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Geometric Representation of Association between Categories
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PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE
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Self-citationContour approximation of data and the harmonic mean
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Azam, Z., Islam, M. M., & Huda, M. N. (2023) · IEEE Access · doi:10.1109/access.2023.3296444 · Cited by 265 · see citing works
- Authors
- Ben-Israel, A., & Iyigun, C.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Ben-Israel, Adi
- ORCID
- Ben-Israel, Adi
- Venue
- Journal of Classification
- Published
- 2008-06
- Volume
- 25
- Issue
- 1
- Pages
- 5-26
- ISSN
- 0176-4268 (ISSN-L)
- 1432-1343
- OpenAlex
- W2056305270
- Cited by
- 74
- References
- 17
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 4 · 2020: 4 · 2019: 5 · 2018: 2 · 2017: 1 · 2016: 7 · 2015: 4 · 2014: 5 · 2013: 6 · 2012: 2
- FWCI
- 8.99
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Journal of Classification (publishedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- OpenMETU (Middle East Technical University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- probabilistic clustering, cluster centers, cluster membership probability, Mahalanobis distance
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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