Update Readme

Add max_features > n_features test
Add make doc

stree/Strees.py

@@ -653,12 +653,12 @@ class Stree(BaseEstimator, ClassifierMixin):
         self.n_features_ = X.shape[1]
         self.n_features_in_ = X.shape[1]
         self.max_features_ = self._initialize_max_features()
-        self.tree_ = self.train(X, y, sample_weight, 1, "root")
+        self.tree_ = self._train(X, y, sample_weight, 1, "root")
         self.X_ = X
         self.y_ = y
         return self
 
-    def train(
+    def _train(
         self,
         X: np.ndarray,
         y: np.ndarray,
@@ -723,10 +723,10 @@ class Stree(BaseEstimator, ClassifierMixin):
             node.make_predictor()
             return node
         node.set_up(
-            self.train(X_U, y_u, sw_u, depth + 1, title + f" - Up({depth+1})")
+            self._train(X_U, y_u, sw_u, depth + 1, title + f" - Up({depth+1})")
         )
         node.set_down(
-            self.train(
+            self._train(
                 X_D, y_d, sw_d, depth + 1, title + f" - Down({depth+1})"
             )
         )
@@ -892,6 +892,12 @@ class Stree(BaseEstimator, ClassifierMixin):
         elif self.max_features is None:
             max_features = self.n_features_
         elif isinstance(self.max_features, numbers.Integral):
+            if self.max_features > self.n_features_:
+                raise ValueError(
+                    "Invalid value for max_features. "
+                    "It can not be greater than number of features "
+                    f"({self.n_features_})"
+                )
             max_features = self.max_features
         else:  # float
             if self.max_features > 0.0:

stree/__init__.py

@@ -6,6 +6,5 @@ __author__ = "Ricardo Montañana Gómez"
 __copyright__ = "Copyright 2020-2021, Ricardo Montañana Gómez"
 __license__ = "MIT License"
 __author_email__ = "ricardo.montanana@alu.uclm.es"
-__url__ = "https://github.com/doctorado-ml/stree"
 
 __all__ = ["Stree", "Snode", "Siterator", "Splitter"]

stree/tests/Stree_test.py

@@ -269,6 +269,12 @@ class Stree_test(unittest.TestCase):
             with self.assertRaises(ValueError):
                 _ = clf._initialize_max_features()
 
+    def test_wrong_max_features(self):
+        X, y = load_dataset(n_features=15)
+        clf = Stree(max_features=16)
+        with self.assertRaises(ValueError):
+            clf.fit(X, y)
+
     def test_get_subspaces(self):
         dataset = np.random.random((10, 16))
         y = np.random.randint(0, 2, 10)