/**

@page wagon_test_manual wagon_test
@brief *Test CART models*
@tableofcontents

@section synopsis Synopsis

@SYNOPSIS@

`wagon_test` is used to test CART models on feature data.

A detailed description of the CART model can be found in the
\ref cart-overview section.


@section options Options

@OPTIONS@

@section wagon_test-testing Testing trees

Decision trees generated by wagon (or otherwise) can be applied
to and tested against data sets using this program.  This program
requires a data set which is in the same format as wagon (and
other programs) requires.  It also needs a dataset description
file naming the fields and given their type (see 
\ref wagon_manual for a description for the actual format.

    wagon_test -data feats.data -desc feats.desc -tree feats.tree

This will simply uses the tree against each sample in the data
file and compare the predicted value with the actual value and
produce a summary of the result.  For categorial predictees a
percentage correct and confusion matrix is generated.  For continuous
values the root mean squared error (RMSE) and correlation between the
predicted values and the actual values is given.  

By default the predictee is the first field but may also be specified
on the command line.  The dataset may contain features which are not
used by the tree.

This program can also be used to generate output values for sampled
data.  In this case the sample data must still contain a "value" for
the predictee even if it is dummy.  The option
`-predict` will output the new sample vector with
the predicted value in place, and the option
`-predict_val` option will just output the value.

This program is specifically designed for testing purposes although it
can also just be used for prediction. It is probably more efficient
to use the Lisp function `wagon` or underlying
C++ function wagon_predict().

*/
