implement ClassificationReport class

src/Phpml/Metric/ClassificationReport.php

@@ -0,0 +1,148 @@
+<?php
+declare(strict_types = 1);
+
+namespace Phpml\Metric;
+
+class ClassificationReport
+{
+    /**
+     * @var array
+     */
+    private $precision = [];
+
+    /**
+     * @var array
+     */
+    private $recall = [];
+
+    /**
+     * @var array
+     */
+    private $f1score = [];
+
+    /**
+     * @var array
+     */
+    private $support = [];
+
+    /**
+     * @var array
+     */
+    private $average = [];
+
+    /**
+     * @param array $actualLabels
+     * @param array $predictedLabels
+     */
+    public function __construct(array $actualLabels, array $predictedLabels)
+    {
+        $truePositive = $falsePositive = $falseNegative = $this->support = self::getLabelIndexedArray($actualLabels);
+
+        foreach ($actualLabels as $index => $actual) {
+            $predicted = $predictedLabels[$index];
+            $this->support[$actual]++;
+
+            if($actual === $predicted) {
+                $truePositive[$actual]++;
+            } else {
+                $falsePositive[$predicted]++;
+                $falseNegative[$actual]++;
+            }
+        }
+
+        $this->computeMetrics($truePositive, $falsePositive, $falseNegative);
+        $this->computeAverage();
+    }
+
+    /**
+     * @return array
+     */
+    public function getPrecision()
+    {
+        return $this->precision;
+    }
+
+    /**
+     * @return array
+     */
+    public function getRecall()
+    {
+        return $this->recall;
+    }
+
+    /**
+     * @return array
+     */
+    public function getF1score()
+    {
+        return $this->f1score;
+    }
+
+    /**
+     * @return array
+     */
+    public function getSupport()
+    {
+        return $this->support;
+    }
+
+    /**
+     * @return array
+     */
+    public function getAverage()
+    {
+        return $this->average;
+    }
+
+    /**
+     * @param array $truePositive
+     * @param array $falsePositive
+     * @param array $falseNegative
+     */
+    private function computeMetrics(array $truePositive, array $falsePositive, array $falseNegative)
+    {
+        foreach ($truePositive as $label => $tp) {
+            $this->precision[$label] = $tp / ($tp + $falsePositive[$label]);
+            $this->recall[$label] = $tp / ($tp + $falseNegative[$label]);
+            $this->f1score[$label] = $this->computeF1Score((float)$this->precision[$label], (float)$this->recall[$label]);
+        }
+    }
+
+    private function computeAverage()
+    {
+        foreach (['precision', 'recall', 'f1score'] as $metric) {
+            $values = array_filter($this->$metric);
+            $this->average[$metric] = array_sum($values) / count($values);
+        }
+    }
+
+    /**
+     * @param float $precision
+     * @param float $recall
+     *
+     * @return float
+     */
+    private function computeF1Score(float $precision, float $recall): float
+    {
+        if(0 == ($divider = $precision+$recall)) {
+            return 0.0;
+        }
+
+        return 2.0 * (($precision * $recall) / ($divider));
+    }
+
+    /**
+     * @param array $labels
+     *
+     * @return array
+     */
+    private static function getLabelIndexedArray(array $labels): array
+    {
+        $labels = array_values(array_unique($labels));
+        sort($labels);
+        $labels = array_combine($labels, array_fill(0, count($labels), 0));
+
+        return $labels;
+    }
+
+}

tests/Phpml/Metric/ClassificationReportTest.php

@@ -0,0 +1,32 @@
+<?php
+declare(strict_types = 1);
+
+namespace tests\Phpml\Metric;
+
+use Phpml\Metric\ClassificationReport;
+
+class ClassificationReportTest extends  \PHPUnit_Framework_TestCase
+{
+
+    public function testClassificationReportGenerateWithStringLabels()
+    {
+        $labels = ['cat', 'ant', 'bird', 'bird', 'bird'];
+        $predicted =  ['cat', 'cat', 'bird', 'bird', 'ant'];
+
+        $report = new ClassificationReport($labels, $predicted);
+
+        $precision = ['cat' => 0.5, 'ant' => 0.0, 'bird' => 1.0];
+        $recall = ['cat' => 1.0, 'ant' => 0.0, 'bird' => 0.67];
+        $f1score = ['cat' => 0.67, 'ant' => 0.0, 'bird' => 0.80];
+        $support = ['cat' => 1, 'ant' => 1, 'bird' => 3];
+        $average = ['precision' => 0.75, 'recall' => 0.83, 'f1score' => 0.73];
+
+
+        $this->assertEquals($precision, $report->getPrecision(), '', 0.01);
+        $this->assertEquals($recall, $report->getRecall(), '', 0.01);
+        $this->assertEquals($f1score, $report->getF1score(), '', 0.01);
+        $this->assertEquals($support, $report->getSupport(), '', 0.01);
+        $this->assertEquals($average, $report->getAverage(), '', 0.01);
+    }
+
+}