Question:
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» c. minimizes the within class variance for a given number of clusters |
Note: |
The above multiple-choice question is for all general and Competitive Exams in India. |