Unsupervised evaluation can be internal or external. Which of the following is an internal method for evaluating alternative clusterings produced by the K-Means algorithm?
A) Use a production rule generator to compare the rule sets generated for each clustering.
B) Compute and compare class resemblance scores for the clusters formed by each clustering.
C) Compare the sum of squared error differences between instances and their corresponding cluster centers for each alternative clustering.
D) Create and compare the decision trees determined by each alternative clustering.

Question

Quizplus · Accepted Answer

Comparing the sum of squared error differences between instances and their corresponding cluster centers is an internal method for evaluating alternative clusterings produced by the K-Means algorithm. This method does not require external knowledge or datasets. Options A, B, and D are all external methods as they require comparing the clustering results to external sources.

Unsupervised Evaluation Can Be Internal or External