Senior Scikit-learn

Test your Senior-level Artificial Intelligence Machine Learning Scikit Learn skills in Emerging Technologies. This timed assessment evaluates your expertise in Information Technology.

Duration: 5 minutes

•40 questions

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40 questions remaining

Question 1 of 40Assessment

When performing clustering, why is the Silhouette Coefficient often preferred over the Inertia (Sum of Squared Errors) for evaluating the optimal number of clusters?

A. Inertia is not defined for density-based clustering algorithms like DBSCAN or OPTICS.

B. The Silhouette Coefficient is less computationally expensive to calculate for large-scale datasets.

C. Inertia decreases monotonically with the number of clusters, making it difficult to find a clear optimum.

D. The Silhouette Coefficient accounts for the volume of the feature space rather than just point distances.

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