The following graphic shows the results of an unsupervised, machine-learning clustering model: k is the number of clusters, and n is the processing time required to run the model. Which of the…

The correct answer is B. 10. The curve shows a steep drop in processing time up to about k = 10, after which gains in speed taper off. Choosing 10 clusters balances sufficient model complexity with reasonable computational cost.

Machine Learning

Question

The following graphic shows the results of an unsupervised, machine-learning clustering model:

k is the number of clusters, and n is the processing time required to run the model. Which of the following is the best value of k to optimize both accuracy and processing requirements?

Exhibit

Options

How the community answered

(37 responses)

A
3% (1)
B
84% (31)
C
5% (2)
D
8% (3)

Explanation

The curve shows a steep drop in processing time up to about k = 10, after which gains in speed taper off. Choosing 10 clusters balances sufficient model complexity with reasonable computational cost.

Topics

#k-means clustering#elbow method#hyperparameter tuning#unsupervised learning

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