不是supervised learning嗎

问题如下：

Which of the following machine learning techniques is most appropriate for executing Step 2:

选项：

K-Means Clustering

Principal Components Analysis (PCA)

Classification and Regression Trees (CART)

解释：

A is correct. K-Means clustering is an unsupervised machine learning algorithm which repeatedly partitions observations into a fixed number, k, of non-overlapping clusters (i.e., groups).

B is incorrect. Principal Components Analysis is a long-established statistical method for dimension reduction, not clustering. PCA aims to summarize or reduce highly correlated features of data into a few main, uncorrelated composite variables.

C is incorrect. CART is a supervised machine learning technique that is most commonly applied to binary classification or regression.