The word chosen by the documentation is a bit confusing.

It says “*Opposite of the value of X on the K-means objective.*”

It means negative of the K-means objective.

**K-Means Objective**

The objective in the K-means is to reduce the sum of squares of the distances of points from their respective cluster centroids. It has other names like J-Squared error function, J-score or within-cluster sum of squares. This value tells how internally coherent the clusters are. (The less the better)

The objective function can be directly obtained from the following method.

`model.inertia_`