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lib/AI/XGBoost/Booster.pm  view on Meta::CPAN

=item dtrain

Training data (AI::XGBoost::DMatrix)

=back

=head2 boost

Boost one iteration using your own gradient

=head3 Parameters

=over 4

=item dtrain

Training data (AI::XGBoost::DMatrix)

=item grad

Gradient of your objective function (Reference to an array)

=item hess

Hessian of your objective function, that is, second order gradient (Reference to an array)

=back

=head2 predict

Predict data using the trained model

=head3 Parameters

=over 4

=item data

Data to predict

=back

=head2 set_param

Set booster parameter

=head3 Example

    $booster->set_param('objective', 'binary:logistic');

=head2 set_attr

Set a string attribute

=head2 get_attr

Get a string attribute

=head2 get_score

Get importance of each feature

=head3 Parameters

=over 4

=item importance_type

Type of importance. Valid values:

=over 4

=item weight

Number of times a feature is used to split the data across all trees

=item gain

Average gain of the feature when it is used in trees

=item cover

Average coverage of the feature when it is used in trees

=back

=item fmap

Name of feature map file

=back

=head2 get_dump

=head2 attributes

Returns all attributes of the booster as a HASHREF

=head2 TO_JSON

Serialize the booster to JSON.

This method is to be used with the option C<convert_blessed> from L<JSON>.
(See L<https://metacpan.org/pod/JSON#OBJECT-SERIALISATION>)

Warning: this API is subject to changes

=head2 BUILD

Use new, this method is just an internal helper

=head2 DEMOLISH

Internal destructor. This method is called automatically

=head1 AUTHOR

Pablo Rodríguez González <pablo.rodriguez.gonzalez@gmail.com>

=head1 COPYRIGHT AND LICENSE

Copyright (c) 2017 by Pablo Rodríguez González.

=cut