Machine Learning

Gaussian Mixture Models

Probabilistic models that represent data as a mixture of Gaussian distributions.

A Gaussian mixture model assumes that the data was generated by several overlapping Gaussian distributions. Each distribution represents a possible cluster with its own centre, spread and probability.

Instead of assigning every observation to exactly one cluster, the model produces membership probabilities. This makes it useful when groups overlap or when uncertainty about cluster assignment matters.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression

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