Generalized Additive Models in Python with a Bayesian twist
A Generalized additive model is a predictive mathematical model defined as a sum of terms that are calibrated (fitted) with observation data. Generalized additive models form a surprisingly general framework for building models for both production software and scientific research. This Python package offers tools for building the model terms as decompositions of various basis functions. It is possible to model the terms e.g. as Gaussian processes (with reduced dimensionality) of various kernels, as piecewise linear functions, and as B-splines, […]
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