Question 31
Domain 1 — AI Concepts, Terminology, and Use CasesWhat is the primary objective of k-means clustering?
Correct answer: E
Explanation
K-means clustering is an unsupervised learning method whose main goal is to group data points into clusters based on similarity. It works by minimizing the distance between points and their assigned cluster centroid, so the primary objective is clustering.
Why each option is right or wrong
A. Classification
B. Association Rule Learning
C. Regression
D. Dimensionality Reduction
E. Clustering
K-means is an unsupervised learning algorithm defined by its objective function: it partitions a dataset into k groups by assigning each observation to the nearest centroid and iteratively updating those centroids to reduce within-cluster sum of squares. In standard formulations, the algorithm minimizes \u2211\u2225x_i - \u03bc_{c_i}\u2225^2, so its purpose is to form coherent groups rather than predict labels or estimate a target variable.
F. Anomaly Detection