package gpr

  1. Overview
  2. Docs
Legend:
Library
Module
Module type
Parameter
Class
Class type

Sub-modules for learning without derivatives.

module Spec = Spec.Eval

Specification of covariance function

Evaluating inducing inputs

Evaluating single inputs

Evaluating (multiple) inputs

(Untrained) model - does not require targets

Trained model - requires targets

module Stats : sig ... end

Statistics derived from trained models

module Mean_predictor = Variational_FITC.Eval.Mean_predictor

Module for making mean predictions

Posterior mean for a single input

Posterior means for (multiple) inputs

module Co_variance_predictor = Variational_FITC.Eval.Co_variance_predictor

Module for making (co-)variance predictions

Posterior variance for a single input

Posterior variances for (multiple) inputs

module Covariances : sig ... end

Posterior covariances

Module for sampling single points from the posterior distribution

module Cov_sampler : sig ... end

Module for sampling (multiple) points from the posterior distribution accounting for their covariance

OCaml

Innovation. Community. Security.