You have a dataset consisting of eight observations: D $=\{$x$1,$x$2,$x$3,$x$4,$x$5,$x$6,$x$7,$x$8\}.$ Additionally, each observation contains a class label. Observations x$1,$ x$3$ and x$4$ belong to class $0$; observations x$2$ and x$8$ belong to class $1$; observation x$5$ belongs to class $2$; observations x$6$ and x$7$ belong to class $3.$

Assume that you have performed K$-$means and have clustered all observations into the three clusters: C$1=\{$x$1,$ x$3,$ x$5\},$ C$2=\{$x$2,$ x$8\}$ and C$3=\{$x$4,$ x$6,$ x$7\}.$

Assign classes to these clusters, based on the majority value of the class attribute within each cluster. Discuss a problem which you observe. What would be the difference if you run K$-$means with $8$ clusters $($K$=8)?$ You do not need to run the algorithm in this case.