KNN (#944)

Creates an example of KNN algorithm using sklearn library.

machine_learning/knn_sklearn.py

@@ -0,0 +1,28 @@
+from sklearn.model_selection import train_test_split
+from sklearn.datasets import load_iris
+from sklearn.neighbors import KNeighborsClassifier
+
+#Load iris file
+iris = load_iris()
+iris.keys()
+
+
+print('Target names: \n {} '.format(iris.target_names))
+print('\n Features: \n {}'.format(iris.feature_names))
+
+#Train set e Test set
+X_train, X_test, y_train, y_test = train_test_split(iris['data'],iris['target'], random_state=4)
+
+#KNN
+
+knn = KNeighborsClassifier (n_neighbors = 1)
+knn.fit(X_train, y_train)
+
+#new array to test
+X_new = [[1,2,1,4],
+		 [2,3,4,5]]	
+
+prediction = knn.predict(X_new)
+
+print('\nNew array: \n {}'
+	  '\n\nTarget Names Prediction: \n {}'.format(X_new, iris['target_names'][prediction]))