What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?

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Question: What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?

Options:

Correct Answer: GMM can handle non-spherical clusters

Solution:

GMM can model clusters with different shapes and sizes, unlike K-Means which assumes spherical clusters.

What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?

What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?

Step 1: Understand that K-Means is a clustering method that groups data into clusters based on their distance from the center of each cluster.
Step 2: Recognize that K-Means assumes all clusters are spherical and of similar size, which can limit its effectiveness.
Step 3: Learn that Gaussian Mixture Models (GMM) can represent clusters that are not just spherical but can have different shapes and sizes.
Step 4: Realize that GMM uses a probabilistic approach, allowing it to better fit the data and capture the underlying distribution of the clusters.

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