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Affinity Propagation/Evidence
Method evidence record

Affinity Propagation

Affinity propagation, introduced by Brendan Frey and Delbert Dueck in 2007, is a clustering algorithm that identifies representative 'exemplars' among the data by exchanging messages between every pair of points until a consistent set of clusters emerges. Unlike k-means it does not require the number of clusters to be specified in advance — that number arises from the data and a 'preference' parameter — and it works directly from pairwise similarities, which need not be a metric.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Affinity Propagation Clustering
Taxonomic method record · ml-model / machine-learning
  • Frey, B. J., & Dueck, D. (2007). Clustering by passing messages between data points. Science, 315(5814), 972–976. · DOI 10.1126/science.1136800
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Curated claims

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyDBSCANmachine-suggested · Relational suggestion, not evidence.Same method familyHierarchical Clusteringmachine-suggested · Relational suggestion, not evidence.Same method familyK-Means Clusteringmachine-suggested · Relational suggestion, not evidence.Same method familySpectral Clusteringmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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