Compute Within-Cluster Sum of Squares

Usage

compute_wss(object, newdata = NULL)

Arguments

object: (any)
Class inheriting from "kmeans".
newdata: (matrix())
New data to predict on.

Details

WSS is defined as $$ \sum_{i=1}^{n} \left\|x_{i} - \mu_{j(i)}\right\|^2 $$, where $x_{i}$ is a data point and $\mu_{j(i)}$ is the centroid of the cluster to which $x_{i}$ is assigned. When new data is provided, the function predicts the nearest cluster for each new observation and computes the WSS for these points based on their predicted clusters.

Examples

km <- kmeans(mtcars, 5)
compute_wss(km)
#> [1]   208.0365  6355.5813 46659.3172  3616.8297  7256.4492
# or with new data
compute_wss(km, mtcars)
#> [1]   208.0365  6355.5813 46659.3172  3616.8297  7256.4492