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or

  $S_AND_W

These stand for "Needleman and Wunsch" and "Smith and
Waterman" respectively.  Any other value will cause an error.

=back

=item svm_rs_cdata MODEL NATIVE SCOR_SET RS_PARAM CVTYPE

*EXPERIMENTAL!*

The function returns an array of training vectors suitable
for use in training a support vector machine (libSVM.pm) or
some other machine learning procedure. Its form is :

  [ [label_class, [(feature vector)], .. ]

The scheme for calculating the training vectory is given

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distance matrices computed between MODEL and NATIVE).

Scheme 0 works as follows :
(see scoranlys.c:get_svmdata for details at the moment).

=item svm_rsfeat MODEL SCOR_SET RS_PARAMS CVTYPE

This returns a set of feature vectors for each position in
MODEL, calculated from local sequence-structure fitness and
residue-specific interaction terms according to the CVTYPE
scheme (see svm_rs_cdata or scoranlys.c for details).  The
form is as follows :

  my @m_fvset = svm_rsfeat MODEL, SCOR_SET, PARAMS, 0
  @m_fvset is of form
    [ (undef), [feature vector], .., .., (undef)]
  and (scalar @m_fvset) == coord_size(MODEL)

undefs are given for positions in the model where a full
feature vector cannot be computed (at the ends, for instance).