GaussianNB test passes + [wip] SVC test

Author: eloquentarduino

.DS_Store

@@ -3,4 +3,7 @@ __pycache__
 *.py[cod]
 .cache
 .ipynb_checkpoints
-everywhereml/project
+everywhereml/project
+serve.py
+test
+notebook.html

.gitignore

@@ -56,4 +56,27 @@ The package implements most of the tools you need to develop a fully functional
 
 Each of these components can be trained in Python and exported to any of the supported languages
 with no (or as few as possible) external dependencies.
-    
+
+For example:
+
+```
+from everywhereml.data.preprocessing import MinMaxScaler
+from sklearn.datasets import load_iris
+
+transformer = MinMaxScaler()
+X, y = load_iris(return_X_y=True)
+Xt, yt = transformer.fit_transform(X, y)
+
+print('Original range', (X.min(), X.max()))
+print('Transformed range', (Xt.min(), Xt.max()))
+
+# port to C++
+print(transformer.port(language='cpp'))
+
+# port to Js
+print(transformer.port(language='js'))
+
+# port to PHP
+print(transformer.port(language='php'))
+```
+

README.md

@@ -5,7 +5,7 @@
    "id": "2801fb1a",
    "metadata": {},
    "source": [
-    "# everywhereml.data.preprocessing.BoxCox\n",
+    "# BoxCox\n",
     "\n",
     "See [sklearn.preprocessing.PowerTransformer](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html).\n",
     "\n",