use v6;
use NativeCall;
use Algorithm::LibSVM::Node;
use Algorithm::LibSVM::Parameter;

unit class Algorithm::LibSVM::Model:auth<zef:titsuki>:ver<0.0.16> is export is repr('CPointer'); 

my constant $library = %?RESOURCES<libraries/svm>.Str;

my sub svm_get_svm_type(Algorithm::LibSVM::Model --> int32) is native($library) { * }
my sub svm_get_nr_class(Algorithm::LibSVM::Model --> int32) is native($library) { * }
my sub svm_get_labels(Algorithm::LibSVM::Model, CArray[int32]) is native($library) { * }
my sub svm_get_sv_indices(Algorithm::LibSVM::Model, CArray[int32]) is native($library) { * }
my sub svm_get_nr_sv(Algorithm::LibSVM::Model --> int32) is native($library) { * }
my sub svm_get_svr_probability(Algorithm::LibSVM::Model --> num64) is native($library) { * }
my sub svm_predict_values(Algorithm::LibSVM::Model, Algorithm::LibSVM::Node, CArray[num64] --> num64) is native($library) { * }
my sub svm_predict(Algorithm::LibSVM::Model, Algorithm::LibSVM::Node --> num64) is native($library) { * }
my sub svm_predict_probability(Algorithm::LibSVM::Model, Algorithm::LibSVM::Node, CArray[num64] --> num64) is native($library) { * }
my sub svm_free_model_content(Algorithm::LibSVM::Model) is native($library) { * }
my sub svm_free_and_destroy_model(Algorithm::LibSVM::Model) is native($library) { * }
my sub svm_check_probability_model(Algorithm::LibSVM::Model --> int32) is native($library) { * }

sub svm_save_model(Str, Algorithm::LibSVM::Model) is native($library) is export { * }

method save(Str $filename) {
    svm_save_model($filename, self)
}

method svm-type(--> SVMType) {
    SVMType(svm_get_svm_type(self))
}

method nr-class(--> Int:D) {
    svm_get_nr_class(self)
}

method labels(--> List) {
    my $labels = CArray[int32].allocate: self.nr-class;
    svm_get_labels(self, $labels);
    $labels.list
}

method sv-indices(--> List) {
    my $indices = CArray[int32].allocate: self.nr-sv;
    svm_get_sv_indices(self, $indices);
    $indices.list
}

method nr-sv(--> Int:D) {
    svm_get_nr_sv(self)
}

method svr-probability(--> Num:D) {
    svm_get_svr_probability(self)
}

method !make-node-linked-list(:$features --> Algorithm::LibSVM::Node) {
    my Algorithm::LibSVM::Node $next .= new(index => -1, value => 0e0);
    for @($features).sort({ $^b.key <=> $^a.key }) {
        $next = Algorithm::LibSVM::Node.new(index => .key, value => .value.Num, next => $next);
    }
    $next;
}

method predict(:$features where { .all ~~ Pair }, Bool :$probability, Bool :$decision-values --> Hash) {
    my %result;
    if $probability and self.check-probability-model {
        my $prob-estimates = CArray[num64].allocate: self.nr-class;
        my $label = svm_predict_probability(self, self!make-node-linked-list(:$features), $prob-estimates);
        %result<label> = $label;
        %result<prob-estimates> = $prob-estimates.list;
    }
    if $decision-values {
        my $dec-values = CArray[num64].allocate: self.nr-class * (self.nr-class - 1) div 2;
        my $label = svm_predict_values(self, self!make-node-linked-list(:$features), $dec-values);
        %result<label> = $label;
        %result<decision-values> = $dec-values.list;
    }

    if not $probability and not $decision-values {
        %result<label> = svm_predict(self, self!make-node-linked-list(:$features));
    }
    %result;
}

method check-probability-model(--> Bool) {
    my $ok = Bool(svm_check_probability_model(self) == 0 ?? False !! True);
    if not $ok {
        die "ERROR: Given model cannot compute probability.";
    }
    $ok;
}

# submethod DESTROY {
#     svm_free_and_destroy_model(self)
# }



head

Algorithm::LibSVM::Model - A Raku Algorithm::LibSVM::Model class


Algorithm::LibSVM::Model is a Raku Algorithm::LibSVM::Model class


Saves the model to the file C<$filename>.


Returns the indices of the support vectors.


Returns the number of the support vectors.


Returns the probability predicted by support vector regression.


method predict(:$features where { .all ~~ Pair }, Bool :$probability, Bool :$decision-values --> Hash)


Conducts the prediction and returns its results.


This library is free software; you can redistribute it and/or modify it under the terms of the MIT License.


libsvm ( https://github.com/cjlin1/libsvm ) by Chih-Chung Chang and Chih-Jen Lin is licensed under the BSD 3-Clause License.


root

Node

Grammar

React

=begin React :component<HeaderCol> :id<menu> 
=para L<Documentation|/doc/introduction>
=para L<Modules| /mods>
=para L<Examples| file:../examples/index.podlite>
=para L<Download |file:../download/index.podlite>
=para L<About|file:../about/index.podlite>
=para 🔍 K<⌘K>/K<ctrl-K>
=end React


=begin React :component<HeaderCol> :id<footer>  
=begin nested :!nested
=item1 B<Language>
    =item2 L<Get started|file:../getting-started/getting-started.podlite>
    =item2 L<Why Raku?|/doc/language/faq#Why-should-I-learn-Raku-What's-so-great-about-it>
    =item2 L<Try Raku|https://glot.io/new/raku>
    =item2 L<Raku cheat sheet|https://github.com/Raku/mu/blob/master/docs/Perl6/Cheatsheet/cheatsheet.txt>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<Raku on Exercism|https://exercism.org/tracks/raku>
    =item2 L<Wikipedia|https://en.wikipedia.org/wiki/Raku_(programming_language)>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>

=end nested
=begin nested :!nested

=item1 B<L<Documentation|/doc>>
    =item2 L<Getting started, Migration guides from other languages, & Tutorials | file:../doc/introduction.podlite>
    =item2 L<Language References|file:../doc/reference.podlite>
    =item2 L<Type Reference| file:../doc/types.podlite>
    =item2 L<Miscellaneous| file:../doc/miscellaneous.podlite>
    =item2 L<FAQs (Frequently Asked Questions)|/doc/language/faq>
    =item2 L<Community|/doc/language/community>
    =item2 L<The list of all documents|file:../doc/index.podlite>

=item1 B<Resources>
    =item2 L<The Raku Guide|https://raku.guide/>
    =item2 L<Books |https://perl6book.com/>
    =item2 L<Rosetta Code | https://www.raku.org/community/rosettacode>

=end nested
=begin nested :!nested

=item1 B<Resoures>
    =item2 L<Download | file:../download/index.podlite>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>

=item1 B<Learning>
    =item2 L<The Raku Guide|https://raku.guide/>
    =item2 L<Wikibook |https://en.wikibooks.org/wiki/Raku_Programming>
    =item2 L<Books |https://perl6book.com/>
    =item2 L<Rosetta Code | https://www.raku.org/community/rosettacode>
    =item2 L<Learn Raku in Y minutes|https://learnxinyminutes.com/docs/raku/>
    =item2 L<Golfing |https://github.com/AlexDaniel/raku-golf-cheatsheet>
=end nested
=begin nested :!nested

=item1 B<Explore>
    =item2 L<Raku Blog Aggregator|https://planet.raku.org/>
    =item2 L<Rakudo Weekly|https://rakudoweekly.blog/>
    =item2 L<The Weekly Challenge |https://perlweeklychallenge.org/>
    =item2 L<Raku Advent Calendar|https://raku-advent.blog/>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>
    =item2 L<empty|#>

=end nested
=end React


=begin React :component<CookieConsent> :id<CookieConsent> :buttonCaption("Got it!")
=para
This website uses cookies for analytics.
=end React


Model

NAME

SYNOPSIS

DESCRIPTION

METHODS

save

svm-type

nr-class

labels

sv-indices

nr-sv

svr-probability

predict

AUTHOR

COPYRIGHT AND LICENSE

Algorithm::LibSVM v0.0.16

Authors

License

Dependencies

Test Dependencies

Provides

Documentation