view release on metacpan or  search on metacpan

lib/AI/Perceptron/Simple.pm  view on Meta::CPAN

Value is C<0>

=back

This subroutine should be called in the procedural way for now.

=cut

sub _tune {
    my $self = shift; 
    my ( $stimuli_hash_ref, $tuning_status ) = @_;

    my %dendrites = $self->get_attributes;

    for ( keys %dendrites ) {
        if ( $tuning_status == TUNE_DOWN ) {
            
            if ( $stimuli_hash_ref->{ $_ } ) { # must check this one, it must be 1 before we can alter the actual dendrite size in the nerve :)
                $self->{ attributes_hash_ref }{ $_ } -= $self->learning_rate;
            }
            #print $_, ": ", $self->{ attributes_hash_ref }{ $_ }, "\n";
            
        } elsif ( $tuning_status == TUNE_UP ) {
            
            if ( $stimuli_hash_ref->{ $_ } ) {
                $self->{ attributes_hash_ref }{ $_ } += $self->learning_rate;
            }
            #print $_, ": ", $self->{ attributes_hash_ref }{ $_ }, "\n";
            
        }
    }

}

=head1 VALIDATION RELATED METHODS

All the validation methods here have the same parameters as the actual C<validate> method and they all do the same stuff. They are also used in the same way.

=head2 take_mock_exam (...)

=head2 take_lab_test (...)

=head2 validate ( \%options )

This method validates the perceptron against another set of data after it has undergone the training process.

This method calculates the output of each row of data and write the result into the predicted column. The data begin written into the new file or the original file will maintain it's sequence.

Please take note that this method will load all the data of the validation stimuli, so please split your stimuli into multiple files if possible and call this method a few more times.

For C<%options>, the followings are needed unless mentioned:

=over 4

=item stimuli_validate => $csv_file

This is the CSV file containing the validation data, make sure that it contains a column with the predicted values as it is needed in the next key mentioned: C<predicted_column_index>

=item predicted_column_index => $column_number

This is the index of the column that contains the predicted output values. C<$index> starts from C<0>.

This column will be filled with binary numbers and the full new data will be saved to the file specified in the C<results_write_to> key.

=item results_write_to => $new_csv_file

Optional.

The default behaviour will write the predicted output back into C<stimuli_validate> ie the original data. The sequence of the data will be maintained.

=back

I<*This method will call C<_real_validate_or_test> to do the actual work.>

=cut

sub take_mock_exam {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

sub take_lab_test {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

sub validate {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

=head1 TESTING RELATED SUBROUTINES/METHODS

All the testing methods here have the same parameters as the actual C<test> method and they all do the same stuff. They are also used in the same way.

=head2 take_real_exam (...)

=head2 work_in_real_world (...)

=head2 test ( \%options )

This method is used to put the trained nerve to the test. You can think of it as deploying the nerve for the actual work or maybe putting the nerve into an empty brain and see how 
well the brain survives :)

This method works and behaves the same way as the C<validate> method. See C<validate> for the details.

I<*This method will call &_real_validate_or_test to do the actual work.>

=cut

# redirect to _real_validate_or_test
sub take_real_exam {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

sub work_in_real_world {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

sub test {
    my ( $self, $data_hash_ref ) = @_;
    $self->_real_validate_or_test( $data_hash_ref );
}

=head2 _real_validate_or_test ( $data_hash_ref )

This is where the actual validation or testing takes place. 

C<$data_hash_ref> is the list of parameters passed into the C<validate> or C<test> methods.

This is a B<method>, so use the OO way. This is one of the exceptions to the rules where private subroutines are treated as methods :)

=cut

sub _real_validate_or_test {

    my $self = shift;   my $data_hash_ref = shift;
    
    #####
    my @missing_keys;
    for ( qw( stimuli_validate predicted_column_index ) ) {
        push @missing_keys, $_ unless exists $data_hash_ref->{ $_ };
    }
    
    croak "Missing keys: @missing_keys" if @missing_keys;
    #####
    
    my $stimuli_validate = $data_hash_ref->{ stimuli_validate };
    my $predicted_index = $data_hash_ref->{ predicted_column_index };
    
    # actual processing starts here
    my $output_file = defined $data_hash_ref->{ results_write_to } 
                        ? $data_hash_ref->{ results_write_to }
                        : $stimuli_validate;
    
    # open for writing results
    my $aoa = csv (in => $stimuli_validate, encoding => ":encoding(utf-8)");
    
    my $attrib_array_ref = shift @$aoa; # 'remove' the header, it's annoying :)

    $aoa = _fill_predicted_values( $self, $stimuli_validate, $predicted_index, $aoa );

    # put back the array of headers before saving file
    unshift @$aoa, $attrib_array_ref;

    print "Saving data to $output_file\n";
    csv( in => $aoa, out => $output_file, encoding => ":encoding(utf-8)" );
    print "Done saving!\n";

}

=head2 &_fill_predicted_values ( $self, $stimuli_validate, $predicted_index, $aoa )

This is where the filling in of the predicted values takes place. Take note that the parameters naming are the same as the ones used in the C<validate> and C<test> method.

This subroutine should be called in the procedural way.

=cut

sub _fill_predicted_values {
    my ( $self, $stimuli_validate, $predicted_index, $aoa ) = @_;

    # CSV processing is all according to the documentation of Text::CSV
    open my $data_fh, "<:encoding(UTF-8)", $stimuli_validate 
        or croak "Can't open $stimuli_validate: $!";
    
    my $csv = Text::CSV->new( {auto_diag => 1, binary => 1} );
    
    my $attrib = $csv->getline($data_fh);
    
    $csv->column_names( $attrib );

    # individual row
    my $row = 0;
    while ( my $data = $csv->getline_hr($data_fh) ) {
        
        if ( _calculate_output( $self, $data )  >= $self->threshold ) {
            # write 1 into aoa
            $aoa->[ $row ][ $predicted_index ] = 1;
        } else {
            #write 0 into aoa
            $aoa->[ $row ][ $predicted_index ] = 0;
        }
        
        $row++;
    }
    
    close $data_fh;
    
    $aoa;
}