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Mr. Dubey • 53.05K Points
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Q. 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

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