Implement LabelEncoder (#369)

CHANGELOG.md

@@ -4,6 +4,10 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+### Added
+- [Preprocessing] Implement LabelEncoder
+
 ## [0.8.0] - 2019-03-20
 ### Added
 - [Tokenization] Added NGramTokenizer (#350)

README.md

@@ -100,6 +100,7 @@ Public datasets are available in a separate repository [php-ai/php-ml-datasets](
 * Preprocessing
     * [Normalization](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/normalization/)
     * [Imputation missing values](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/imputation-missing-values/)
+    * LabelEncoder
 * Feature Extraction
     * [Token Count Vectorizer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/token-count-vectorizer/)
         * NGramTokenizer

docs/index.md

@@ -85,6 +85,7 @@ Example scripts are available in a separate repository [php-ai/php-ml-examples](
 * Preprocessing
     * [Normalization](machine-learning/preprocessing/normalization.md)
     * [Imputation missing values](machine-learning/preprocessing/imputation-missing-values.md)
+    * LabelEncoder
 * Feature Extraction
     * [Token Count Vectorizer](machine-learning/feature-extraction/token-count-vectorizer.md)
     * [Tf-idf Transformer](machine-learning/feature-extraction/tf-idf-transformer.md)

src/Preprocessing/LabelEncoder.php

@@ -0,0 +1,47 @@
+<?php
+
+declare(strict_types=1);
+
+namespace Phpml\Preprocessing;
+
+final class LabelEncoder implements Preprocessor
+{
+    /**
+     * @var int[]
+     */
+    private $classes = [];
+
+    public function fit(array $samples, ?array $targets = null): void
+    {
+        $this->classes = [];
+
+        foreach ($samples as $sample) {
+            if (!isset($this->classes[(string) $sample])) {
+                $this->classes[(string) $sample] = count($this->classes);
+            }
+        }
+    }
+
+    public function transform(array &$samples): void
+    {
+        foreach ($samples as &$sample) {
+            $sample = $this->classes[(string) $sample];
+        }
+    }
+
+    public function inverseTransform(array &$samples): void
+    {
+        $classes = array_flip($this->classes);
+        foreach ($samples as &$sample) {
+            $sample = $classes[$sample];
+        }
+    }
+
+    /**
+     * @return string[]
+     */
+    public function classes(): array
+    {
+        return array_keys($this->classes);
+    }
+}

tests/Preprocessing/LabelEncoderTest.php

@@ -0,0 +1,68 @@
+<?php
+
+declare(strict_types=1);
+
+namespace Phpml\Tests\Preprocessing;
+
+use Phpml\Preprocessing\LabelEncoder;
+use PHPUnit\Framework\TestCase;
+
+final class LabelEncoderTest extends TestCase
+{
+    /**
+     * @dataProvider labelEncoderDataProvider
+     */
+    public function testFitAndTransform(array $samples, array $transformed): void
+    {
+        $le = new LabelEncoder();
+        $le->fit($samples);
+        $le->transform($samples);
+
+        self::assertEquals($transformed, $samples);
+    }
+
+    public function labelEncoderDataProvider(): array
+    {
+        return [
+            [['one', 'one', 'two', 'three'], [0, 0, 1, 2]],
+            [['one', 1, 'two', 'three'], [0, 1, 2, 3]],
+            [['one', null, 'two', 'three'], [0, 1, 2, 3]],
+            [['one', 'one', 'one', 'one'], [0, 0, 0, 0]],
+            [['one', 'one', 'one', 'one', null, null, 1, 1, 2, 'two'], [0, 0, 0, 0, 1, 1, 2, 2, 3, 4]],
+        ];
+    }
+
+    public function testResetClassesAfterNextFit(): void
+    {
+        $samples = ['Shanghai', 'Beijing', 'Karachi'];
+
+        $le = new LabelEncoder();
+        $le->fit($samples);
+
+        self::assertEquals(['Shanghai', 'Beijing', 'Karachi'], $le->classes());
+
+        $samples = ['Istanbul', 'Dhaka', 'Tokyo'];
+
+        $le->fit($samples);
+
+        self::assertEquals(['Istanbul', 'Dhaka', 'Tokyo'], $le->classes());
+    }
+
+    public function testFitAndTransformFullCycle(): void
+    {
+        $samples = ['Shanghai', 'Beijing', 'Karachi', 'Beijing', 'Beijing', 'Karachi'];
+        $encoded = [0, 1, 2, 1, 1, 2];
+
+        $le = new LabelEncoder();
+        $le->fit($samples);
+
+        self::assertEquals(['Shanghai', 'Beijing', 'Karachi'], $le->classes());
+
+        $transformed = $samples;
+        $le->transform($transformed);
+        self::assertEquals($encoded, $transformed);
+
+        $le->inverseTransform($transformed);
+        self::assertEquals($samples, $transformed);
+    }
+}