ScholarGate
Asistenti

Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Inercia×Indeksi Calinski-Harabasz×
FushaVlerësimi i modeleveVlerësimi i modeleve
FamiljaMCDMMCDM
Viti i origjinës19671974
KrijuesiStuart Lloyd, James MacQueenTadeusz Calinski, Jerzy Harabasz
LlojiClustering quality metricCluster quality metric
Burimi themeluesLloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1-27. DOI ↗
Emërtime të tjeraWCSS, within-cluster sum of squares, cluster cohesionvariance ratio criterion, pseudo F-statistic, CH index
Të lidhura55
PërmbledhjaInertia, 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 Calinski-Harabasz Index, also called the Variance Ratio Criterion, was introduced by Calinski and Harabasz in 1974. It is a metric that measures the ratio of between-cluster variance to within-cluster variance, adjusted for the number of clusters and data points. Higher values indicate better-separated, more compact clusters.
ScholarGateSeti i të dhënave
  1. v1
  2. 2 Burimet
  3. PUBLISHED
  1. v1
  2. 1 Burimet
  3. PUBLISHED

Shko te kërkimi Shkarko diapozitivat

ScholarGateKrahasoni metodat: Inertia (Within-Cluster Sum of Squares) · Calinski-Harabasz Index. Marrë më 2026-06-20 nga https://scholargate.app/sq/compare