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This package provides classes\nfor:\n\n1) Modeling / clustering a dataset using a finite mixture of multivariate Student's\nt distributions fit via the EM algorithm. This is analogous to scikit-learn's \nGaussianMixture.\n2) Modeling / clustering a dataset using a mixture of multivariate Student's \nt distributions fit via the variational mean-field approximation. This is analogous to\nscikit-learn's BayesianGaussianMixture.\n\n### Installation\n\n    pip install studenttmixture\n\nStarting with version 1.11, this is a pure Python package so installation\nshould be very straightforward.\n\nDependencies are numpy, scipy and scikit-learn.\n\n### Usage\n\n- [EMStudentMixture](https://github.com/jlparkI/mix_T/blob/main/docs/Finite_Mixture_Docs.md)\u003cbr\u003e\n- [VariationalStudentMixture](https://github.com/jlparkI/mix_T/blob/main/docs/Variational_Mixture_Docs.md)\u003cbr\u003e\n- [Tutorial: Modeling with mixtures](https://github.com/jlparkI/mix_T/blob/main/docs/Tutorial.md)\u003cbr\u003e\n\n### Background\n\n- [Deriving the mean-field formula](https://github.com/jlparkI/mix_T/blob/main/docs/variational_mean_field.pdf)\u003cbr\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjlparki%2Fmix_t","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjlparki%2Fmix_t","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjlparki%2Fmix_t/lists"}