Algorithm-DecisionTree

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lib/Algorithm/BoostedDecisionTree.pm  view on Meta::CPAN

#--------------------------------------------------------------------------------------
# Copyright (c) 2017 Avinash Kak. All rights reserved.  This program is free
# software.  You may modify and/or distribute it under the same terms as Perl itself.
# This copyright notice must remain attached to the file.
#
# Algorithm::BoostedDecisionTree is a Perl module for boosted decision-tree based
# classification of multidimensional data.
# -------------------------------------------------------------------------------------

#use lib 'blib/lib', 'blib/arch';

#use 5.10.0;
use strict;
use warnings;
use Carp;
use Algorithm::DecisionTree 3.43;
use List::Util qw(reduce min max);

our $VERSION = '3.43';

lib/Algorithm/DecisionTreeWithBagging.pm  view on Meta::CPAN

#--------------------------------------------------------------------------------------
# Copyright (c) 2017 Avinash Kak. All rights reserved.  This program is free
# software.  You may modify and/or distribute it under the same terms as Perl itself.
# This copyright notice must remain attached to the file.
#
# Algorithm::DecisionTreeWithBagging is a Perl module for incorporating bagging in
# decision tree construction and in classification using decision trees.
# -------------------------------------------------------------------------------------

#use lib 'blib/lib', 'blib/arch';

#use 5.10.0;
use strict;
use warnings;
use Carp;
use Algorithm::DecisionTree 3.43;

our $VERSION = '3.43';

############################################   Constructor  ##############################################

lib/Algorithm/RandomizedTreesForBigData.pm  view on Meta::CPAN

#--------------------------------------------------------------------------------------
# Copyright (c) 2017 Avinash Kak. All rights reserved.  This program is free
# software.  You may modify and/or distribute it under the same terms as Perl itself.
# This copyright notice must remain attached to the file.
#
# Algorithm::RandomizedTreesForBigData is a Perl module for inducing multiple decision
# trees using randomized selection of samples from a large training data file.
# -------------------------------------------------------------------------------------

#use lib 'blib/lib', 'blib/arch';

#use 5.10.0;
use strict;
use warnings;
use Carp;
use List::Util qw(pairmap);
use Algorithm::DecisionTree 3.43;

our $VERSION = '3.43';

lib/Algorithm/RegressionTree.pm  view on Meta::CPAN

#--------------------------------------------------------------------------------------
# Copyright (c) 2017 Avinash Kak. All rights reserved.  This program is free
# software.  You may modify and/or distribute it under the same terms as Perl itself.
# This copyright notice must remain attached to the file.
#
# Algorithm::RegressionTree is a Perl module for constructing regression trees.  It calls
# on the main Algorithm::DecisionTree module for some of its functionality.
# -------------------------------------------------------------------------------------

#use lib 'blib/lib', 'blib/arch';

#use 5.10.0;
use strict;
use warnings;
use Carp;
use File::Basename;
use Algorithm::DecisionTree 3.43;
use List::Util qw(reduce min max pairmap sum);
use Math::GSL::Matrix;
use Graphics::GnuplotIF;

t/test.t  view on Meta::CPAN

use Test::Simple tests => 2;

use lib '../blib/lib','../blib/arch';

use Algorithm::DecisionTree;

# Test 1 (Digest Parameter File and Generate Training Data):

my $parameter_file = "t/param.txt";
my $output_training_datafile = "t/__trainingdata.csv";

my $data_gen = TrainingDataGeneratorSymbolic->new( 
                              output_training_datafile => $output_training_datafile,