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Gaussian processes

Introduction to the Tpros software

This introduction is especially aimed at users of the bigback Bayesian neural network simulator. The Tpros software and its rudimentary manual are found at

Like bigback, Tpros is a program that is run from the unix prompt and which reads its information from a spec file and from the command line. Tpros is considerably more flexible than bigback. The user can arrange the spec file information in a logical hierarchy of files, with a master file which includes other sub-files. And minor changes to the operation of the program can be effected by adding command-line arguments, rather than having to create new spec files.

As in bigback, data files are plain ascii files arranged in columns. Training sets and test sets should be arranged in separate files.

Whereas bigback was accompanied by a second set of programs called generate**, which were used to create predictions from a trained neural network, Tpros is a single program which can be run in several modes, one of which creates predictions. The other two modes optimize the hyperparameters for a given training data set, and optimize the *inputs* so as to maximize the expectation of some function of the *output*.

How to use Tpros

The usage is sketched in the file `TManual' and also if you type
The most important arguments which you may want to change on the command line are as follows:
-tf         specify target file
-gf         specify grid file
-ntdat      specify number of data points

-nv         specify initial noise variance        
-tol        specify macopt tolerance          

-opt        optimise hyperparameters
-NOopt      don't optimise hyperparameters

-hi         specify hyperparameter input file
-ho         specify hyperparameter output file

-ninter     specify number of interpolation points
-int_tf     specify interpolation target file
-int_gf     specify interpolation grid file
-int_of     specify interpolation output file
-int_eb     calculate error bars
          BIGBACK name:   TPROS name:
          targets         targets
          inputs          grid file (gf)
          sigma_w         hyperparameters
          test set        interpolation	      
          `generate'      interpolation
          output file     output file
          sigma_nu^2      noise variance (nv)
          linmintol       tol
Typical usage
In a typical project, I might go through the following steps.
David MacKay <>
Last modified: Sat Jul 12 18:22:13 2003