NAME

AI::ConfusionMatrix - make a confusion matrix

SYNOPSIS

my %matrix;

Loop over your tests

---

$matrix{$expected}{$predicted} += 1;

---

makeConfusionMatrix(\%matrix, 'output.csv');

DESCRIPTION

This module prints a confusion matrix from a hash reference. This module tries to be generic enough to be used within a lot of machine learning projects.

Function

makeConfusionMatrix($hash_ref, $file [, $delimiter ])

This function makes a confusion matrix from $hash_ref and writes it to $file. $file can be a filename or a file handle opened with the w+ mode. If $delimiter is present, it is used as a custom separator for the fields in the confusion matrix.

Examples:

makeConfusionMatrix(\%matrix, 'output.csv');
makeConfusionMatrix(\%matrix, 'output.csv', ';');
makeConfusionMatrix(\%matrix, *$fh);

The hash reference must look like this :

$VAR1 = {


          'value_expected1' => {
                      'value_predicted1' => value
                    },
          'value_expected2' => {
                      'value_predicted1' => value,
                      'value_predicted2' => value
                    },
          'value_expected3' => {
                      'value_predicted3' => value
                    }

        };

The output will be in CSV. Here is an example:

,1974,1978,2002,2003,2005,TOTAL,TP,FP,FN,SENS,ACC
1974,3,1,,,2,6,3,4,3,42.86%,50.00%
1978,1,5,,,,6,5,4,1,55.56%,83.33%
2002,2,2,8,,,12,8,1,4,88.89%,66.67%
2003,1,,,7,2,10,7,0,3,100.00%,70.00%
2005,,1,1,,6,8,6,4,2,60.00%,75.00%
TOTAL,7,9,9,7,10,42,29,13,13,69.05%,69.05%

Prettified:

|       | 1974 | 1978 | 2002 | 2003 | 2005 | TOTAL | TP | FP | FN | SENS    | ACC    |
|-------|------|------|------|------|------|-------|----|----|----|---------|--------|
| 1974  | 3    | 1    |      |      | 2    | 6     | 3  | 4  | 3  | 42.86%  | 50.00% |
| 1978  | 1    | 5    |      |      |      | 6     | 5  | 4  | 1  | 55.56%  | 83.33% |
| 2002  | 2    | 2    | 8    |      |      | 12    | 8  | 1  | 4  | 88.89%  | 66.67% |
| 2003  | 1    |      |      | 7    | 2    | 10    | 7  | 0  | 3  | 100.00% | 70.00% |
| 2005  |      | 1    | 1    |      | 6    | 8     | 6  | 4  | 2  | 60.00%  | 75.00% |
| TOTAL | 7    | 9    | 9    | 7    | 10   | 42    | 29 | 13 | 13 | 69.05%  | 69.05% |

TP:

True Positive

FP:

False Positive

FN:

False Negative

SENS

Sensitivity. Number of true positives divided by the number of positives.

ACC:

Accuracy

AUTHOR

Vincent Lequertier <vi.le@autistici.org>

LICENSE

This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself.