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lib/AI/XGBoost/CAPI/RAW.pm  view on Meta::CPAN

=head2 XGBoosterUpdateOneIter

Update the model in one round using dtrain

Parameters:

=over 4

=item handle 

handle

=item iter

current iteration rounds

=item dtrain

training data

=back

=head2 XGBoosterEvalOneIter

=head2 XGBoosterPredict

Make prediction based on dmat

Parameters:

=over 4

=item handle 

handle

=item dmat 

data matrix

=item option_mask 

bit-mask of options taken in prediction, possible values

=over 4

=item

0: normal prediction

=item

1: output margin instead of transformed value

=item

2: output leaf index of trees instead of leaf value, note leaf index is unique per tree

=item

4: output feature contributions to individual predictions

=back

=item ntree_limit 

limit number of trees used for prediction, this is only valid for boosted trees
when the parameter is set to 0, we will use all the trees

=item out_len 

used to store length of returning result

=item out_result 

used to set a pointer to array

=back

=head2 XGBoosterLoadModel

Load model form existing file

Parameters:

=over 4

=item handle

handle

=item fname

file name

=back

=head2 XGBoosterSaveModel

Save model into existing file

Parameters:

=over 4

=item handle

handle

=item fname

file name

=back

=head2 XGBoosterLoadModelFromBuffer

=head2 XGBoosterGetModelRaw

=head2 XGBoosterDumpModel