create docs for tf-idf transformer

CHANGELOG.md

@@ -9,7 +9,7 @@ This changelog references the relevant changes done in PHP-ML library.
 
 * 0.1.1 (2016-07-12)
     * feature [Cross Validation] Stratified Random Split - equal distribution for targets in split
-    * feature [General] Documentation - add missing pages and fix links
+    * feature [General] Documentation - add missing pages (Pipeline, ConfusionMatrix and TfIdfTransformer) and fix links 
 
 * 0.1.0 (2016-07-08)
     * first develop release

README.md

@@ -59,6 +59,7 @@ composer require php-ai/php-ml
     * [Imputation missing values](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/imputation-missing-values/)
 * Feature Extraction
     * [Token Count Vectorizer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/token-count-vectorizer/)
+    * [Tf-idf Transformer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/tf-idf-transformer/)
 * Datasets
     * [CSV](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/csv-dataset/)
     * Ready to use:

docs/index.md

@@ -59,6 +59,7 @@ composer require php-ai/php-ml
     * [Imputation missing values](machine-learning/preprocessing/imputation-missing-values/)
 * Feature Extraction
     * [Token Count Vectorizer](machine-learning/feature-extraction/token-count-vectorizer/)
+    * [Tf-idf Transformer](machine-learning/feature-extraction/tf-idf-transformer/)
 * Datasets
     * [CSV](machine-learning/datasets/csv-dataset/)
     * Ready to use:

docs/machine-learning/feature-extraction/tf-idf-transformer.md

@@ -0,0 +1,42 @@
+# Tf-idf Transformer
+
+Tf–idf, short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus.
+
+### Constructor Parameters
+
+* $samples (array) - samples for fit tf-idf model
+
+```
+use Phpml\FeatureExtraction\TfIdfTransformer;
+
+$samples = [
+    [1, 2, 4],
+    [0, 2, 1]
+];
+
+$transformer = new TfIdfTransformer($samples);
+```
+
+### Transformation
+
+To transform a collection of text samples use `transform` method. Example:
+
+```
+use Phpml\FeatureExtraction\TfIdfTransformer;
+
+$samples = [
+    [0 => 1, 1 => 1, 2 => 2, 3 => 1, 4 => 0, 5 => 0],
+    [0 => 1, 1 => 1, 2 => 0, 3 => 0, 4 => 2, 5 => 3],
+];
+        
+$transformer = new TfIdfTransformer($samples);
+$transformer->transform($samples);
+
+/*
+$samples = [
+   [0 => 0, 1 => 0, 2 => 0.602, 3 => 0.301, 4 => 0, 5 => 0],
+   [0 => 0, 1 => 0, 2 => 0, 3 => 0, 4 => 0.602, 5 => 0.903],
+];
+*/
+        
+```

mkdocs.yml

@@ -25,6 +25,7 @@ pages:
       - Imputation missing values: machine-learning/preprocessing/imputation-missing-values.md
     - Feature Extraction:
       - Token Count Vectorizer: machine-learning/feature-extraction/token-count-vectorizer.md
+      - Tf-idf Transformer: machine-learning/feature-extraction/tf-idf-transformer.md
     - Datasets:
       - Array Dataset: machine-learning/datasets/array-dataset.md
       - CSV Dataset: machine-learning/datasets/csv-dataset.md

tests/Phpml/FeatureExtraction/TfIdfTransformerTest.php

@@ -10,7 +10,7 @@ class TfIdfTransformerTest extends \PHPUnit_Framework_TestCase
 {
     public function testTfIdfTransformation()
     {
-        //https://en.wikipedia.org/wiki/Tf%E2%80%93idf
+        // https://en.wikipedia.org/wiki/Tf-idf
 
         $samples = [
             [0 => 1, 1 => 1, 2 => 2, 3 => 1, 4 => 0, 5 => 0],