Which of the following are examples of unsupervised learning:

A. Regression

B. Clustering

C. Classification

Question

Which of the following are examples of unsupervised learning:

A. Regression

B. Clustering

C. Classification

BlackTom AI · Accepted Answer

To evaluate which options correspond to unsupervised learning, we need to recall the definitions of common machine learning paradigms.
Option A: Regression. This task involves predicting a continuous numerical target based on input features, and it typically requires labeled data (input-output pairs) to learn the mapping. Therefore, regression is a classic example of supervised learning, not unsupervised.
Option B: Clustering. Clustering aims to group similar data points together without using any labeled targets. The algorithm discovers structure in unlabeled data, which is the hallmark of unsupervised learning. This option is consistent with unsupervised learning.
Option C: Classification. Classification assigns data points to predefined categories using labeled examples during training. Since it relies on labeled targets to learn decision boundaries, it is another staple of supervised learning rather than unsupervised.
In summary, among the given choices, clustering fits the unsupervised learning paradigm, while regression and classification fall under supervised learning. The listed options present combinations that reflect this distinction, with only the clustering component aligning with unsupervised methods.

ISBA2401 - Data Analytics with Python (MW 05:45 PM, MW 7:35 PM, TTh 7:35PM) Quiz 4- Requires Respondus LockDown Browser

Which of the following are examples of unsupervised learning: A. Regression B. Clustering C. Classification

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