Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.

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A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

Predictive microbiology models explain bacterial number variations over time and how growth/inactivation rates are affected by environmental conditions (Lammerding and Fazil, 2000). In the development ...

To streamline the interpretation of vibrational spectra, this work introduces the use of Bayesian linear regression with automatic relevance determination as a viable approach to decompose the atomic ...

This repository contains Python/PyMC3 code for a selection of models and figures from the book 'Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan', Second Edition, by John Kruschke (2015 ...