142 lines
3.4 KiB
PHP
142 lines
3.4 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Metric;
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class ClassificationReport
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{
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/**
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* @var array
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*/
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private $precision = [];
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/**
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* @var array
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*/
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private $recall = [];
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/**
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* @var array
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*/
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private $f1score = [];
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/**
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* @var array
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*/
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private $support = [];
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/**
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* @var array
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*/
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private $average = [];
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public function __construct(array $actualLabels, array $predictedLabels)
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{
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$truePositive = $falsePositive = $falseNegative = $this->support = self::getLabelIndexedArray($actualLabels, $predictedLabels);
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foreach ($actualLabels as $index => $actual) {
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$predicted = $predictedLabels[$index];
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++$this->support[$actual];
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if ($actual === $predicted) {
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++$truePositive[$actual];
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} else {
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++$falsePositive[$predicted];
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++$falseNegative[$actual];
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}
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}
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$this->computeMetrics($truePositive, $falsePositive, $falseNegative);
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$this->computeAverage();
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}
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public function getPrecision() : array
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{
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return $this->precision;
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}
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public function getRecall() : array
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{
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return $this->recall;
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}
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public function getF1score() : array
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{
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return $this->f1score;
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}
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public function getSupport() : array
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{
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return $this->support;
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}
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public function getAverage() : array
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{
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return $this->average;
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}
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private function computeMetrics(array $truePositive, array $falsePositive, array $falseNegative): void
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{
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foreach ($truePositive as $label => $tp) {
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$this->precision[$label] = $this->computePrecision($tp, $falsePositive[$label]);
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$this->recall[$label] = $this->computeRecall($tp, $falseNegative[$label]);
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$this->f1score[$label] = $this->computeF1Score((float) $this->precision[$label], (float) $this->recall[$label]);
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}
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}
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private function computeAverage(): void
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{
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foreach (['precision', 'recall', 'f1score'] as $metric) {
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$values = array_filter($this->{$metric});
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if (empty($values)) {
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$this->average[$metric] = 0.0;
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continue;
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}
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$this->average[$metric] = array_sum($values) / count($values);
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}
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}
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/**
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* @return float|string
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*/
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private function computePrecision(int $truePositive, int $falsePositive)
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{
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if (0 == ($divider = $truePositive + $falsePositive)) {
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return 0.0;
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}
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return $truePositive / $divider;
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}
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/**
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* @return float|string
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*/
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private function computeRecall(int $truePositive, int $falseNegative)
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{
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if (0 == ($divider = $truePositive + $falseNegative)) {
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return 0.0;
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}
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return $truePositive / $divider;
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}
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private function computeF1Score(float $precision, float $recall) : float
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{
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if (0 == ($divider = $precision + $recall)) {
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return 0.0;
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}
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return 2.0 * (($precision * $recall) / $divider);
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}
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private static function getLabelIndexedArray(array $actualLabels, array $predictedLabels) : array
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{
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$labels = array_values(array_unique(array_merge($actualLabels, $predictedLabels)));
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sort($labels);
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$labels = array_combine($labels, array_fill(0, count($labels), 0));
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return $labels;
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}
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}
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