Welcome to PyGP

This package provides Gaussian Process based regression. Find provided regression modules in pygp.gp.

Documentation API Contents:

• Gaussian Process (GP) Regression
  • Gaussian Process Package
  • Grouping GP regression classes
  • Class for Gaussian process classification using EP
• Covariance Functions
  • Covariance Function Combinators
  • Squared Exponential Covariance functions
  • Noise covariance function
  • Classes for linear covariance function
• GP Hyperparameter optimization
  • Package for Gaussian Process Optimization
• Hyperprior Distributions
  • Hyperpriors for log likelihood calculation
• Plotting gpr output
  • pygp plotting tools

See following examples for usage details:

• Example for GP regression with hyperparameter optimization
• Example for GP regression with hyperparameter optimization and input shift adjustment

Indices and tables

• Index
• Module Index
• Search Page