Simplify examples

examples/joblib_example.py

@@ -6,6 +6,8 @@ except ImportError:
 from sklearn import datasets
 from sklearn.linear_model import LogisticRegression
 from sklearn.model_selection import train_test_split
+import numpy as np
+import matplotlib.pyplot as plt
 
 
 from trains import Task
@@ -25,4 +27,19 @@ joblib.dump(model, 'model.pkl', compress=True)
 
 loaded_model = joblib.load('model.pkl')
 result = loaded_model.score(X_test, y_test)
-print(result)
+x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
+y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5
+h = .02  # step size in the mesh
+xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
+plt.figure(1, figsize=(4, 3))
+
+plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)
+plt.xlabel('Sepal length')
+plt.ylabel('Sepal width')
+
+plt.xlim(xx.min(), xx.max())
+plt.ylim(yy.min(), yy.max())
+plt.xticks(())
+plt.yticks(())
+
+plt.show()