The total within-cluster sum of squares measures the compactness of the clustering by summing the squared Euclidean distances of each observation to its cluster centroid across all clusters: \(WSS = \sum_{k=1}^{K} \sum_{i \in C_k} \| x_i - \mu_k \|^2\). Lower values indicate tighter clusters.
Dictionary
This mlr3::Measure can be instantiated via the dictionary mlr3::mlr_measures or with the
associated sugar function mlr3::msr():
Meta Information
Task type: “clust”
Range: \([0, \infty)\)
Minimize: TRUE
Average: macro
Required Prediction: “partition”
Required Packages: mlr3, mlr3cluster
See also
Dictionary of Measures: mlr3::mlr_measures
as.data.table(mlr_measures) for a complete table of all (also dynamically created) mlr3::Measure implementations.
Other cluster measures:
mlr_measures_clust.avg_between,
mlr_measures_clust.avg_within,
mlr_measures_clust.ch,
mlr_measures_clust.davies_bouldin,
mlr_measures_clust.dunn,
mlr_measures_clust.dunn2,
mlr_measures_clust.entropy,
mlr_measures_clust.pearsongamma,
mlr_measures_clust.silhouette,
mlr_measures_clust.wb_ratio