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Hierarchical Clustering/Evidence
Method evidence record

Hierarchical Clustering

Hierarchical clustering is an unsupervised method that groups observations into nested clusters and draws the result as a dendrogram, so the number of clusters need not be fixed in advance. Its agglomerative form rests on the objective-function grouping criterion introduced by Joe Ward in 1963.

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Hierarchical Agglomerative Clustering
Taxonomic method record · ml-model / machine-learning
  • Ward, J. H. (1963). Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association, 58(301), 236–244. · DOI 10.1080/01621459.1963.10500845
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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.See alsoFactor Analysismachine-suggested · Relational suggestion, not evidence.Same method familyGaussian Mixture Modelmachine-suggested · Relational suggestion, not evidence.Same method familyPrincipal Component Analysismachine-suggested · Relational suggestion, not evidence.

Evidence status

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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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