Added a ranking example

examples/ranking_example.py

@@ -0,0 +1,30 @@
+"""
+================
+Ranking example
+================
+"""
+
+import numpy as np
+
+from sklearn.datasets import load_diabetes
+from sklearn.utils.testing import assert_almost_equal
+
+from lightning.ranking import PRank
+from lightning.ranking import KernelPRank
+
+# TODO: Add more datasets.
+bunch = load_diabetes()
+X, y = bunch.data, bunch.target
+y = np.round(y, decimals=-2)
+
+# TODO: Add more rankers.
+rankers = (PRank(n_iter=10, shuffle=False, random_state=0),
+           KernelPRank(kernel="linear",
+	               n_iter=10,
+                       shuffle=True,
+                       random_state=0))
+
+for ranker in rankers:
+	print ranker.__class__.__name__
+	ranker.fit(X, y)
+	print ranker.score(X, y)