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dml.gp
  gp Gaussian process.
 
    DESCRIPTION
 
    Wrapper to the GPstuff Gaussian process code
 
    REFERENCE
     Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki,
     Ville Tolvanen, Aki Vehtari (2013). GPstuff: A Toolbox for Bayesian
     Modeling with Gaussian Processes. In Journal of Machine Learning
     Research, accepted for publication.
 
    EXAMPLE
 
    X = randn(20,2);
    Y = X(:,1);
    m = dml.gp;
    m = m.train(X,Y);
    Z = m.test(X);
 
    DEVELOPER
    Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, Aki Vehtari
Class Details
Superclasses dml.method
Sealed false
Construct on load false
Constructor Summary
gp Gaussian process. 
Property Summary
gproc gaussian process object 
indims dimensions of the input data (excluding the trial dim and time dim in time series data) 
restart when false, starts at the previously learned parameters; needed for online learning and grid search 
verbose whether or not to generate diagnostic output 
Method Summary
  model this method does not return a model 
  test  
  train