MCQOPTIONS
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| 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 | |