saniikakulkarni/Gaussian-Mixture-Model-from-scratch
Implementing Gaussian Mixture Model from scratch using python class and Expectation Maximization algorithm. It is a clustering algorithm having certain advantages over kmeans algorithm.
This project helps data scientists and machine learning engineers group similar data points together. You provide a dataset, and it will output clusters, identifying underlying patterns and segmentations within your data. This is useful for anyone needing to automatically categorize data based on inherent characteristics.
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Use this if you need to automatically discover distinct groups within your data, especially when clusters might overlap or have varying shapes, providing more flexibility than simple grouping methods.
Not ideal if you need a simple, fast clustering solution for clearly separated, spherical clusters, or if you prefer predefined categories rather than discovery.
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Mar 28, 2021
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