1.

The K-means algorithm:

A. requires the dimension of the feature space to be no bigger than the number of samples
B. has the smallest value of the objective function when k = 1
C. minimizes the within class variance for a given number of clusters
D. converges to the global optimum if and only if the initial means are chosen as some of the samples themselves
Answer» D. converges to the global optimum if and only if the initial means are chosen as some of the samples themselves


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