Spam filter classification example (#17)

* Added spam dataset

* Added spam dataset

* complete sms spam classifier

* Fix type and add info to readme

Author: Sezekiel

README.md

@@ -20,6 +20,7 @@ Classification:
 
 * `languageDetection.php` - classifier build for language detection
 * `minst.php` - recognize handwritten digits from MNIST dataset (to download dataset use `bin/download-mnist.sh`)
+* `spamFilter.php` - simple spam filter with example dataset
 
 Regression:
 

classification/spamFilter.php

@@ -0,0 +1,49 @@
+<?php declare(strict_types=1);
+
+namespace PhpmlExamples;
+
+include 'vendor/autoload.php';
+
+use Phpml\Dataset\CsvDataset;
+use Phpml\Dataset\ArrayDataset;
+use Phpml\FeatureExtraction\TokenCountVectorizer;
+use Phpml\Tokenization\WordTokenizer;
+use Phpml\CrossValidation\StratifiedRandomSplit;
+use Phpml\FeatureExtraction\TfIdfTransformer;
+use Phpml\Metric\Accuracy;
+use Phpml\Classification\SVC;
+use Phpml\SupportVectorMachine\Kernel;
+
+//temporarily alter the memory limit for such large dataset
+ini_set('memory_limit', '-1');
+
+echo 'Loading dataset...' . PHP_EOL;
+$dataset = new CsvDataset('data/spam.csv', 1);
+$vectorizer = new TokenCountVectorizer(new WordTokenizer());
+$tfIdfTransformer = new TfIdfTransformer();
+
+echo 'Extracting samples ...' . PHP_EOL;
+$samples = [];
+foreach ($dataset->getSamples() as $sample) {
+    $samples[] = $sample[0];
+}
+
+echo 'Vectorizing samples ...' . PHP_EOL;
+$vectorizer->fit($samples);
+$vectorizer->transform($samples);
+
+$tfIdfTransformer->fit($samples);
+$tfIdfTransformer->transform($samples);
+
+$dataset = new ArrayDataset($samples, $dataset->getTargets());
+
+$randomSplit = new StratifiedRandomSplit($dataset, 0.1);
+
+echo 'Training model ...' . PHP_EOL;
+$classifier = new SVC(Kernel::RBF, 1000);
+$classifier->train($randomSplit->getTrainSamples(), $randomSplit->getTrainLabels());
+
+echo 'Performing prediction ...' . PHP_EOL;
+$predictedLabels = $classifier->predict($randomSplit->getTestSamples());
+
+echo 'Accuracy: '.Accuracy::score($randomSplit->getTestLabels(), $predictedLabels) . PHP_EOL;