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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Inertia×Kiwango cha Silhouette×
NyanjaTathmini ya ModeliTathmini ya Modeli
FamiliaMCDMMCDM
Mwaka wa asili19671987
MwanzilishiStuart Lloyd, James MacQueenPeter Rousseeuw
AinaClustering quality metricCluster quality metric
Chanzo asiliaLloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65. DOI ↗
Majina mbadalaWCSS, within-cluster sum of squares, cluster cohesionsilhouette coefficient, silhouette index
Zinazohusiana55
MuhtasariInertia, also called Within-Cluster Sum of Squares (WCSS), is a measure of cluster cohesion that quantifies how tightly points are grouped around their cluster centroids. Lower values indicate more compact, cohesive clusters. Inertia is the primary objective function for k-means clustering and has been a fundamental metric since the method's introduction.The Silhouette Coefficient, introduced by Peter Rousseeuw in 1987, is a metric that measures how similar an object is to its own cluster compared to other clusters. It ranges from -1 to 1, where values close to 1 indicate well-separated and cohesive clusters, values near 0 suggest overlapping clusters, and negative values indicate misclustered points.
ScholarGateSeti ya data
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  1. v1
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  3. PUBLISHED

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ScholarGateLinganisha mbinu: Inertia (Within-Cluster Sum of Squares) · Silhouette Score. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare