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pod/TrunkClassifier.pod  view on Meta::CPAN

classify a sample, its expression of the probe at the decision level is compared to the
thresholds of outgoing edges. If the expression is less than the first threshold,
class1 is assigned to the sample. If, on the other hand, the expression is greater than
the second threshold, class2 is assigned to the sample. In the case expression is
in-between the thresholds, the algorithm proceeds to the next decision level of the
trunk.

By default, classification is done by leave-one-out cross validation (LOOCV) meaning
that a single sample is used as test set, while the remaining samples are used to build
the classifier. This is done for every sample in the input dataset. See the the algorithm
publication for more details. A PubMed link can be found in L</"SEE ALSO">.

=head2 ARGUMENTS

Following installation, the algorithm can be run from the terminal using the
run_classifier.pl script supplied in the t/ folder. The command should be in this form

C<perl run_classifier.pl [Options] [Input data file]>

=head3 INPUT DATA FILE

pod/TrunkClassifier.pod  view on Meta::CPAN

in the testset.

=item Unable to create output file

Indicates that output files were not writable in the output folder.

=back

=head1 SEE ALSO

The publication describing the algorithm can be found in PubMed by this link:
L<http://www.ncbi.nlm.nih.gov/pubmed?Db=pubmed&Cmd=DetailsSearch&Term=23467331%5Buid%5D>

=head1 EXPORT

None by default. The runClassifier subroutine is exported on request.

=head1 AUTHOR

Benjamin Ulfenborg, E<lt>wolftower85@gmail.comE<gt>