create docs for distance metrics functions

docs/machine-learning/metric/distance/chebyshev.md

@@ -0,0 +1,3 @@
+# Chebyshev
+
+Class for calculation Chebyshev distance.

docs/machine-learning/metric/distance/euclidean.md

@@ -1,17 +1,18 @@
-# Distance
+# Euclidean
 
-Special class for calculation of different types of distance.
+Class for calculation Euclidean distance.
 
 ### Euclidean
 
 ![euclidean](https://upload.wikimedia.org/math/8/4/9/849f040fd10bb86f7c85eb0bbe3566a4.png "Euclidean Distance")
 
-To calculate euclidean distance:
+To calculate distance:
 
 ```
 $a = [4, 6];
 $b = [2, 5];
-        
-Distance::euclidean($a, $b);
+   
+$euclidean = new Euclidean();
+$euclidean->distance($a, $b);
 // return 2.2360679774998
 ```

docs/machine-learning/metric/distance/manhattan.md

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+# Manhattan

docs/machine-learning/metric/distance/minkowski.md

@@ -0,0 +1 @@
+# Minkowski

mkdocs.yml

@@ -13,5 +13,9 @@ pages:
         - Iris: machine-learning/datasets/demo/iris.md
     - Metric:
       - Accuracy: machine-learning/metric/accuracy.md
-      - Distance: machine-learning/metric/distance.md
+      - Distance:
+        - Euclidean: machine-learning/metric/distance/euclidean.md
+        - Chebyshev: machine-learning/metric/distance/chebyshev.md
+        - Manhattan: machine-learning/metric/distance/manhattan.md
+        - Minkowski: machine-learning/metric/distance/minkowski.md
 theme: readthedocs