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Elbow Method/Evidence
Method evidence record

Elbow Method

The Elbow Method is a heuristic for selecting the optimal number of clusters in partitional clustering. Introduced by Robert Thorndike in 1953, it involves fitting clustering models for increasing numbers of clusters and plotting the within-cluster sum of squares (WCSS) against the number of clusters. The 'elbow' occurs where the rate of WCSS decrease sharply changes, suggesting an optimal cluster count.

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Source record

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

Elbow Method for Optimal Cluster Number
Taxonomic method record · mcdm / model-evaluation
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics. · URL
  • Thorndike, R. L. (1953). Who belongs in the family? Psychometrika, 18(4), 267-276. · DOI 10.1007/BF02289263
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Related methods

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

Same method familyCalinski-Harabasz Indexmachine-suggested · Relational suggestion, not evidence.Same method familyDavies-Bouldin Indexmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGap Statisticmachine-suggested · Relational suggestion, not evidence.Same method familyInertia (Within-Cluster Sum of Squares)machine-suggested · Relational suggestion, not evidence.Same method familySilhouette Scoremachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

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

Sources

2 recorded citations, copied from the method source record.

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