Shypd.aiThe largest open index of AI toolssklearn-bayes is a Python package for Bayesian Machine Learning with a scikit-learn API. It provides various Bayesian algorithms for classification, regression, and decomposition tasks.
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sklearn-bayes is a Python package designed for Bayesian Machine Learning, offering a scikit-learn compatible API. This allows developers and data scientists to seamlessly integrate Bayesian methods into their existing machine learning workflows. The package includes a wide array of algorithms such as ARD Models (Relevance Vector Regression/Classification, Type II Maximum Likelihood ARD Linear/Logistic Regression), Decomposition Models (Restricted Boltzmann Machines, Latent Dirichlet Allocation), Linear Models (Empirical Bayes Linear/Logistic Regression, Variational Bayes Linear/Logistic Regression), Mixture Models (Variational Bayes Gaussian/Bernoulli/Dirichlet Process/Poisson Mixture Models), and Hidden Markov Models (Variational Bayes Poisson/Bernoulli/Gaussian Hidden Markov Models). It provides probabilistic alternatives to traditional scikit-learn models, making it suitable for tasks requiring uncertainty quantification and robust model selection.
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