Bayesian Analysis with Python - Second Edition

Dirichlet process

All models that we have seen so far were parametric models. These are models with a fixed number of parameters that we are interested in estimating, like a fixed number of clusters. We can also have non-parametric models, probably a better name for these models will be non-fixed-parametric models, but someone already decided the name for us. Non-parametric models are models with a theoretically infinite number of parameters. In practice, we somehow let the data to reduce the theoretically infinite number of parameters to some finite number, in other words the data decides the actual number of parameters, thus non-parametric models are very flexible. In this book we are going to see two examples of such models: the Gaussian ...