Q. The K-means algorithm: (Solved)
1. requires the dimension of the feature space to be no bigger than the number of samples
2. has the smallest value of the objective function when k = 1
3. minimizes the within class variance for a given number of clusters
4. converges to the global optimum if and only if the initial means are chosen as some of the samples themselves
- c. minimizes the within class variance for a given number of clusters