This code was used in the blog post "What is a Gaussian Mixture Model (GMM) - 3D Point Cloud Classification Primer".
It is composed of three main parts:
- Generating data
- Fitting the Gaussian Mixture Model
- Visualization
You will need to have matplotlib, scikit-learn and ofcourse numpy installed.
The code was tested on Python 3.5.2 on Windows.
Simply run estimate_gmm_sklearn.py.
Change the variable D to be 2 or 3 for 2D or 3D results respectively.