AI-Perceptron-Simple
view release on metacpan - search on metacpan
view release on metacpan or search on metacpan
* make subroutines exportable, the names are too long
* :local_data
* :portable_data
* cleaned & refactored codes
* &display_confusion_matrix
* improved the documentation
Version 1.01 24 AUGUST 2021
* Fixed some technical issues
* fixed test scripts not run in correct sequence
* must be creation -> train -> validate/test
* local::lib issue should be fixed by now
Version 1.00 23 AUGUST 2021
* The following features were implemented over the course of time (see also My::Perceptron v0.04 on github):
* create perceptron
* process data: &train method
* read csv - for training stage
* save and load the perceptron
* output algorithm for train
* read and calculate data line by line
* validate method
* read csv bulk
* write predicted values into original file
* write predicted values into new file
* test method
* read csv bulk
* write predicted values into original file
* write predicted values into new file
* confusion matrix
* read only expected and predicted columns, line by line
AI-Perceptron-Simple (v1.04)
A Newbie Friendly Module to Create, Train, Validate and Test Perceptrons / Neurons
This module provides methods to build, train, validate and test a perceptron. It can also save the data of the perceptron for future use for any actual AI programs.
This module is also aimed to help newbies grasp hold of the concept of perceptron, training, validation and testing as much as possible. Hence, all the methods and subroutines in this module are decoupled as much as possible so that the actual script...
INSTALLATION
To install this module, run the following commands:
perl Makefile.PL
make
make test
docs/AI-Perceptron-Simple-1.04.html view on Meta::CPAN
<li><a href="#train-stimuli_train_csv-expected_output_header-save_nerve_to_file">train ( $stimuli_train_csv, $expected_output_header, $save_nerve_to_file )</a></li>
<li><a href="#train-stimuli_train_csv-expected_output_header-save_nerve_to_file-display_stats-identifier">train ( $stimuli_train_csv, $expected_output_header, $save_nerve_to_file, $display_stats, $identifier )</a></li>
<li><a href="#calculate_output-self-stimuli_hash">&_calculate_output( $self, \%stimuli_hash )</a></li>
<li><a href="#tune-self-stimuli_hash-tune_up_or_down">&_tune( $self, \%stimuli_hash, $tune_up_or_down )</a></li>
</ul>
</li>
<li><a href="#VALIDATION-RELATED-METHODS">VALIDATION RELATED METHODS</a>
<ul>
<li><a href="#take_mock_exam">take_mock_exam (...)</a></li>
<li><a href="#take_lab_test">take_lab_test (...)</a></li>
<li><a href="#validate-options">validate ( \%options )</a></li>
</ul>
</li>
<li><a href="#TESTING-RELATED-SUBROUTINES-METHODS">TESTING RELATED SUBROUTINES/METHODS</a>
<ul>
<li><a href="#take_real_exam">take_real_exam (...)</a></li>
<li><a href="#work_in_real_world">work_in_real_world (...)</a></li>
<li><a href="#test-options">test ( \%options )</a></li>
<li><a href="#real_validate_or_test-data_hash_ref">_real_validate_or_test ( $data_hash_ref )</a></li>
<li><a href="#fill_predicted_values-self-stimuli_validate-predicted_index-aoa">&_fill_predicted_values ( $self, $stimuli_validate, $predicted_index, $aoa )</a></li>
</ul>
</li>
<li><a href="#RESULTS-RELATED-SUBROUTINES-METHODS">RESULTS RELATED SUBROUTINES/METHODS</a>
<ul>
<li><a href="#get_exam_results">get_exam_results ( ... )</a></li>
<li><a href="#get_confusion_matrix-options">get_confusion_matrix ( \%options )</a></li>
<li><a href="#collect_stats-options">&_collect_stats ( \%options )</a></li>
<li><a href="#calculate_total_entries-c_matrix_ref">&_calculate_total_entries ( $c_matrix_ref )</a></li>
<li><a href="#calculate_accuracy-c_matrix_ref">&_calculate_accuracy ( $c_matrix_ref )</a></li>
<li><a href="#calculate_sensitivity-c_matrix_ref">&_calculate_sensitivity ( $c_matrix_ref )</a></li>
docs/specifications.t view on Meta::CPAN
#
# Version 0.01 - completed on 8 August 2021
# [v] able to create perceptron
# [v] able to process data: &train method
# [v] read csv - for training stage
# [v] able to save the actual perceptron object and load it back
#
# Version 0.02 - completed on 17 August 2021
# [v] implement output algorithm for train and finalize it
# [v] read and calculate data line by line, not bulk, so no shuffling method
# [v] implement validate method
# [v] read csv bulk - for validating and testing stages
# [v] write into a new csv file - validation and testing stages
# [v] implement testing method
# [v] read csv bulk - for validating and testing stages
# [v] write into a new csv file - validation and testing stages
#
# Version 0.03 - completed on 19 August 2021
# [v] implement confusion matrix
# [v] read only expected and predicted columns, line by line
# [v] return a hash of data
lib/AI/Perceptron/Simple.pm view on Meta::CPAN
# train
$nerve->tame( ... );
$nerve->exercise( ... );
$nerve->train( $training_data_csv, $expected_column_name, $save_nerve_to );
# or
$nerve->train(
$training_data_csv, $expected_column_name, $save_nerve_to,
$show_progress, $identifier); # these two parameters must go together
# validate
$nerve->take_lab_test( ... );
$nerve->take_mock_exam( ... );
# fill results to original file
$nerve->validate( {
stimuli_validate => $validation_data_csv,
predicted_column_index => 4,
} );
# or
# fill results to a new file
$nerve->validate( {
stimuli_validate => $validation_data_csv,
predicted_column_index => 4,
results_write_to => $new_csv
} );
# test - see "validate" method, same usage
$nerve->take_real_exam( ... );
$nerve->work_in_real_world( ... );
$nerve->test( ... );
# confusion matrix
my %c_matrix = $nerve->get_confusion_matrix( {
full_data_file => $file_csv,
actual_output_header => $header_name,
predicted_output_header => $predicted_header_name,
t/10-test_synonyms_exam.t view on Meta::CPAN
use constant IDENTIFIER => "book_name";
my $nerve_file = $FindBin::Bin . "/perceptron_1.nerve";
ok( -s $nerve_file, "Found nerve file to load" );
my $mature_nerve = AI::Perceptron::Simple::load_perceptron( $nerve_file );
# write to original file
stdout_like {
ok ( $mature_nerve->take_real_exam( {
stimuli_validate => TEST_DATA,
predicted_column_index => 4,
} ),
"Testing stage succedded!" );
} qr/book_list_test\.csv/, "Correct output for testing when saving back to original file";
# with new output file
stdout_like {
ok ( $mature_nerve->take_real_exam( {
stimuli_validate => TEST_DATA,
predicted_column_index => 4,
results_write_to => TEST_DATA_NEW_FILE
} ),
"Testing stage succedded!" );
} qr/book_list_test_exam\-filled\.csv/, "Correct output for testing when saving to NEW file";
ok( -e TEST_DATA_NEW_FILE, "New testing file found" );
isnt( -s TEST_DATA_NEW_FILE, 0, "New output file is not empty" );
t/10-test_synonyms_work.t view on Meta::CPAN
use constant IDENTIFIER => "book_name";
my $nerve_file = $FindBin::Bin . "/perceptron_1.nerve";
ok( -s $nerve_file, "Found nerve file to load" );
my $mature_nerve = AI::Perceptron::Simple::load_perceptron( $nerve_file );
# write to original file
stdout_like {
ok ( $mature_nerve->work_in_real_world( {
stimuli_validate => TEST_DATA,
predicted_column_index => 4,
} ),
"Testing stage succedded!" );
} qr/book_list_test\.csv/, "Correct output for testing when saving back to original file";
# with new output file
stdout_like {
ok ( $mature_nerve->work_in_real_world( {
stimuli_validate => TEST_DATA,
predicted_column_index => 4,
results_write_to => TEST_DATA_NEW_FILE
} ),
"Testing stage succedded!" );
} qr/book_list_test_work\-filled\.csv/, "Correct output for testing when saving to NEW file";
ok( -e TEST_DATA_NEW_FILE, "New testing file found" );
isnt( -s TEST_DATA_NEW_FILE, 0, "New output file is not empty" );
view release on metacpan - search on metacpan
( run in 1.229 second using v1.00-cache-2.02-grep-82fe00e-cpan-24a475fd873 )