AI-ConfusionMatrix
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lib/AI/ConfusionMatrix.pm view on Meta::CPAN
carp ('First argument must be a hash reference') if ref($matrix) ne 'HASH';
my %cmData = genConfusionMatrixData($matrix);
# This ties @output_array to the output file. Each output_array item represents a line in the output file
tie my @output_array, 'Tie::File', $file or carp "$!";
# Empty the file
@output_array = ();
my @columns = @{$cmData{columns}};
map {$output_array[0] .= $delem . $_} join $delem, (@columns, 'TOTAL', 'TP', 'FP', 'FN', 'SENS', 'ACC');
my $line = 1;
my @expected = sort keys %{$matrix};
for my $expected (@expected) {
$output_array[$line] = $expected;
my $lastIndex = 0;
my $index;
for my $predicted (sort keys %{$matrix->{$expected}}) {
# Calculate the index of the label in the output_array of columns
$index = _findIndex($predicted, \@columns);
# Print some of the delimiter to get to the column of the next value predicted
lib/AI/ConfusionMatrix.pm view on Meta::CPAN
$cmData{stats}{$expected}{'tp'},
$cmData{stats}{$expected}{'fp'},
$cmData{stats}{$expected}{'fn'},
sprintf('%.2f%%', $cmData{stats}{$expected}{'sensitivity'}),
sprintf('%.2f%%', $cmData{stats}{$expected}{'acc'})
);
++$line;
}
# Print the TOTAL row to the csv file
$output_array[$line] = 'TOTAL' . $delem;
map {$output_array[$line] .= $cmData{totals}{$_} . $delem} (@columns);
$output_array[$line] .= join $delem, (
$cmData{totals}{'total'},
$cmData{totals}{'tp'},
$cmData{totals}{'fp'},
$cmData{totals}{'fn'},
sprintf('%.2f%%', $cmData{totals}{'sensitivity'}),
sprintf('%.2f%%', $cmData{totals}{'acc'})
);
untie @output_array;
( run in 0.270 second using v1.01-cache-2.11-cpan-49f99fa48dc )