### What is a Gaussian Mixture Model (GMM)?

A Gaussian Mixture Model describes an underlying distribution that is composed of multiple individual Gaussian distributions

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A Gaussian Mixture Model describes an underlying distribution that is composed of multiple individual Gaussian distributions

Expectation-Maximization refers to a two-step, iterative process that is often used when latent or unobserved variables are present underlying a data generation process.

When used for clustering, any of the evaluation metrics (Silhouette Score, Dunn Index, Rand Index, etc.) are appropriate

K-Means aims to minimize the Within Cluster Sum of Squares, while EM aims to maximize the likelihood of an underlying probability distribution.

Pros: Has the ability to find more local clusters that K-Means would not be able to differentiate

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- Machine Learning 101 (30)
- Statistics 101 (38)
- Supervised Learning (113)
- Unsupervised Learning (55)
- Deep Learning (23)
- Data Preparation (37)
- General (7)
- Standardization (6)
- Missing data (7)
- Textual Data (17)