BenchMark Quizzes by MDFT Pro

Identify Example Of Unsupervised Machine Learning

Claire, the Learning Analytics Researcher at MDFT Pro, is exploring different machine learning approaches to analyze student behavior patterns and discover natural groupings in learning data. MDFT Pro, a well-known training agency, has collected extensive data about student engagement, study habits, course completion times, and assessment performance, but doesn’t have predefined categories or labels for different types of learners. Claire wants to use machine learning techniques that can automatically identify hidden patterns and discover distinct student segments without requiring manual labeling or predetermined classifications of learning styles.

Which machine learning approach should Claire use to discover natural groupings in student data without labeled examples?

Choose the correct answer from the options below.

Explanations for each answer:

Classification is incorrect. Classification is supervised learning that requires labeled training data to learn how to categorize new data points into predefined classes.
Regression is incorrect. Regression is supervised learning that uses labeled examples to learn how to predict continuous numeric values from input features.
Clustering is correct. Clustering is unsupervised learning that discovers hidden patterns and groups similar data points together without requiring pre-labeled training examples.
Reinforcement learning is incorrect. Reinforcement learning trains agents through rewards and penalties but isn't typically categorized as unsupervised learning since it uses feedback signals.

Learn more about unsupervised learning:

Unsupervised Learning

Exam Preparation Quiz

Identify Example Of Unsupervised Machine Learning