Which of the following statements is NOT TRUE?

Clustering analysis in unsupervised learning since it does not require labeled training data.

The K$-$means algorithm is sensitive to outliers.

The centroids in the K$-$means algorithm may not be any observed data points.

Wheri clustering, we want to put two similar data objects into the same cluster.

For different initializations, the K$-$means algorithn will always give the same clustering results.