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What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?
Practice Questions
Q1
What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?
GMM can handle non-spherical clusters
GMM is faster
GMM requires fewer parameters
GMM is easier to implement
Questions & Step-by-Step Solutions
What is the main advantage of using Gaussian Mixture Models (GMM) over K-Means?
Steps
Concepts
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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