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lib/Algorithm/LibLinear/Model.pm  view on Meta::CPAN

package Algorithm::LibLinear::Model;

use 5.014;
use Algorithm::LibLinear;  # For Algorithm::LibLinear::Model::Raw
use Algorithm::LibLinear::Types qw/Feature/;
use Carp qw//;
use Smart::Args::TypeTiny;
use Types::Standard qw/ClassName InstanceOf Int Str/;

my $InstanceOfPackage = InstanceOf[__PACKAGE__];

sub new {
    args
        my $class => ClassName,
        my $raw_model => InstanceOf['Algorithm::LibLinear::Model::Raw'];

    bless +{ raw_model => $raw_model, } => $class;
}

sub load {
    args
        my $class => ClassName,
        my $filename => Str;

    my $raw_model = Algorithm::LibLinear::Model::Raw->load($filename);
    $class->new(raw_model => $raw_model);
}

sub bias {
    args_pos
        my $self => $InstanceOfPackage,
        my $label => +{ isa => Int, optional => 1, };

    return $self->raw_model->rho if $self->is_oneclass_model;
    # Non one-class SVM model requires label index.
    Carp::croak('Missing mandatory label index.') unless defined $label;

    $self->raw_model->bias($label - 1);
}

sub class_labels { $_[0]->raw_model->class_labels }

sub coefficient {
    args_pos
        my $self => $InstanceOfPackage,
        my $feature => Int,
        my $label => Int;

    $self->raw_model->coefficient($feature, $label - 1);
}

sub is_oneclass_model { $_[0]->raw_model->is_oneclass_model }

sub is_probability_model { $_[0]->raw_model->is_probability_model }

sub is_regression_model { $_[0]->raw_model->is_regression_model }

sub num_classes { $_[0]->raw_model->num_classes }

sub num_features { $_[0]->raw_model->num_features }

sub predict {
    args
        my $self => $InstanceOfPackage,
        my $feature => Feature;

    $self->raw_model->predict($feature);
}

sub predict_probability {
    args
        my $self => $InstanceOfPackage,
        my $feature => Feature;

    unless ($self->is_probability_model) {
        Carp::carp(
            'This method only makes sense when the model is configured for'