Which of the following statements about ML functional performance metrics is correct?

The correct answer is A. Metrics used to measure clustering include intra-cluster metrics that measure the proximity of a. The ISTQB CT-AI syllabus explains ML performance metrics in Section3.2 - Evaluating ML Models. Forclustering, which is an unsupervised learning method, the syllabus lists metrics such asintra- cluster distance,inter-cluster distance, and coherence measures. Intra-cluster…

Machine Learning (ML)

Question

Options

AMetrics used to measure clustering include intra-cluster metrics that measure the proximity of a
BThe R-squared metric indicates how well the model distinguishes between different classes
CThe silhouette coefficient describes how well the regression model fits the dependent variables.
DThe receiver operating characteristic curve shows, depending on parameters, how well the model

How the community answered

(33 responses)

A
73% (24)
B
18% (6)
C
6% (2)
D
3% (1)

Explanation

The ISTQB CT-AI syllabus explains ML performance metrics in Section3.2 - Evaluating ML Models. Forclustering, which is an unsupervised learning method, the syllabus lists metrics such asintra- cluster distance,inter-cluster distance, and coherence measures. Intra-cluster metrics evaluate how close data points are within a cluster, which directly corresponds to Option A.

Topics

#clustering metrics#silhouette coefficient#ROC curve#regression metrics

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