Which of the following is TRUE about the K$-$Means Clustering process? Check all that apply.

Clusters are stabilized when stopped.

Two most similar clusters are combined into one in each iteration.

Ward's minimum variance is the default distance measure used in JMP Pro.

All objects are placed in one cluster when stopped.

Reassigns each object to a cluster based on the cluster means in each iteration.

A specific number of clusters must be given to start the process.

Each object is assigned to one of the $k$ clusters based on a seed point.

Each object is placed in its own cluster when started.