fixes to tree plot, remove unused function in knn plot

Author: amueller

mglearn/plot_interactive_tree.py

@@ -26,7 +26,6 @@ def tree_image(tree, fout=None):
     dot_data = StringIO()
     export_graphviz(tree, out_file=dot_data, max_depth=3, impurity=False)
     data = dot_data.getvalue()
-    #data = re.sub(r"gini = 0\.[0-9]+\\n", "", dot_data.getvalue())
     data = re.sub(r"samples = [0-9]+\\n", "", data)
     data = re.sub(r"\\nsamples = [0-9]+", "", data)
     data = re.sub(r"value", "counts", data)
@@ -43,8 +42,9 @@ def plot_tree_progressive():
     plt.figure()
     ax = plt.gca()
     discrete_scatter(X[:, 0], X[:, 1], y, ax=ax)
-    ax.set_xticks(())
-    ax.set_yticks(())
+    ax.set_xlabel("Feature 0")
+    ax.set_ylabel("Feature 1")
+    plt.legend(["Class 0", "Class 1"], loc='best')
 
     axes = []
     for i in range(3):

mglearn/plot_kneighbors_regularization.py

@@ -4,14 +4,6 @@
 from sklearn.neighbors import KNeighborsRegressor
 
 
-
-def plot_regression_datasets():
-    fig, axes = plt.subplots(1, 3, figsize=(15, 5))
-    for n_samples, ax in zip([10, 100, 1000], axes):
-        x, y = make_dataset(n_samples)
-        ax.plot(x, y, 'o', alpha=.6)
-
-
 def plot_kneighbors_regularization():
     rnd = np.random.RandomState(42)
     x = np.linspace(-3, 3, 100)
@@ -32,6 +24,7 @@ def plot_kneighbors_regularization():
         ax.legend()
         ax.set_title("n_neighbors = %d" % n_neighbors)
 
+
 if __name__ == "__main__":
     plot_kneighbors_regularization()
     plt.show()