OS Library for Conditional Gaussian Mixture Modelling in Python
Show HN: OS Library for Conditional Gaussian Mixture Modelling in Python
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I've been working on a compact Python library called cgmm for regression modelling with Conditional Gaussian Mixture Models. It allows flexible, data-driven regression beyond Gaussian and linear assumptions.It integrates with scikit-learn, comes with documentation and examples, and is available on PyPI.Key features:* model non-Gaussian conditional distributions* capture non-linear dependencies* handle heteroscedastic noise (variance that changes with inputs)* provide full predictive distributions, not just point estimatesThe current release added:* Mixture of Experts (MoE): Softmax-gated experts with linear mean functions (Jordan & Jacobs, “Hierarchical Mixtures of Experts and the EM Algorit
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Website: cgmm.readthedocs.io/en/latest/GitHub:
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