Algorithm-LibLinear
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{
"abstract" : "A Perl binding for LIBLINEAR, a library for classification/regression using linear SVM and logistic regression.",
"author" : [
"Koichi SATO E<lt>sekia@cpan.orgE<gt>"
],
"dynamic_config" : 1,
"generated_by" : "Module::Build version 0.4231",
"license" : [
"mit"
],
"meta-spec" : {
"url" : "http://search.cpan.org/perldoc?CPAN::Meta::Spec",
---
abstract: 'A Perl binding for LIBLINEAR, a library for classification/regression using linear SVM and logistic regression.'
author:
- 'Koichi SATO E<lt>sekia@cpan.orgE<gt>'
build_requires:
ExtUtils::CBuilder: '0'
Test::Deep: '0'
Test::Exception: '0'
Test::LeakTrace: '0'
Test::More: '0'
configure_requires:
Module::Build: '0.42'
=head1 NAME
Algorithm::LibLinear - A Perl binding for LIBLINEAR, a library for classification/regression using linear SVM and logistic regression.
=head1 SYNOPSIS
use Algorithm::LibLinear;
# Constructs a model for L2-regularized L2 loss support vector classification.
my $learner = Algorithm::LibLinear->new(
cost => 1,
epsilon => 0.01,
solver => 'L2R_L2LOSS_SVC',
weights => [
=head1 SEE ALSO
L<Algorithm::LibLinear::DataSet>
L<Algorithm::LibLinear::FeatureScaling>
L<Algorithm::LibLinear::Model>
L<LIBLINEAR Homepage|http://www.csie.ntu.edu.tw/~cjlin/liblinear/>
L<Algorithm::SVM> - A Perl binding to LIBSVM.
=head1 LICENSE
=head2 Algorithm::LibLinear
Copyright (c) 2013-2023 Koichi SATO. All rights reserved.
The MIT License (MIT)
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modi...
lib/Algorithm/LibLinear.pm view on Meta::CPAN
[ map {
+{ label => $labels->[$_], weight => $weights->[$_], }
} 0 .. $#$labels ];
}
1;
__END__
=head1 NAME
Algorithm::LibLinear - A Perl binding for LIBLINEAR, a library for classification/regression using linear SVM and logistic regression.
=head1 SYNOPSIS
use Algorithm::LibLinear;
# Constructs a model for L2-regularized L2 loss support vector classification.
my $learner = Algorithm::LibLinear->new(
cost => 1,
epsilon => 0.01,
solver => 'L2R_L2LOSS_SVC',
weights => [
lib/Algorithm/LibLinear.pm view on Meta::CPAN
=head1 SEE ALSO
L<Algorithm::LibLinear::DataSet>
L<Algorithm::LibLinear::FeatureScaling>
L<Algorithm::LibLinear::Model>
L<LIBLINEAR Homepage|http://www.csie.ntu.edu.tw/~cjlin/liblinear/>
L<Algorithm::SVM> - A Perl binding to LIBSVM.
=head1 LICENSE
=head2 Algorithm::LibLinear
Copyright (c) 2013-2023 Koichi SATO. All rights reserved.
The MIT License (MIT)
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modi...
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