Practice Gaussian Mixture Models (gmms) (5.4) - Latent Variable & Mixture Models
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Gaussian Mixture Models (GMMs)

Practice - Gaussian Mixture Models (GMMs)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a Gaussian Mixture Model?

💡 Hint: Think about how different groups can be represented as overlapping.

Question 2 Easy

Define soft clustering.

💡 Hint: Consider how a point can have a stronger affiliation to one cluster over another.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a Gaussian Mixture Model (GMM)?

A single Gaussian distribution
A probabilistic model with multiple Gaussian components
A linear regression model

💡 Hint: Consider the essence of mixture models.

Question 2

True or False: GMMs can model soft clustering.

True
False

💡 Hint: Think about how points can have probabilistic memberships to clusters.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset with three distinct but overlapping clusters, describe how you would apply a GMM and the steps you would take.

💡 Hint: Consider how each step builds on the last to refine your clusters.

Challenge 2 Hard

Discuss the limitations of GMMs in practical applications. What scenarios can lead to poor performance?

💡 Hint: Think about the assumptions we make when fitting models to real-world data.

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Reference links

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