Implement iwss feature selection (#45) (#47)

stree/Splitter.py

@@ -271,10 +271,17 @@ class Splitter:
                 f"criteria has to be max_samples or impurity; got ({criteria})"
             )
 
-        if feature_select not in ["random", "best", "mutual", "cfs", "fcbf"]:
+        if feature_select not in [
+            "random",
+            "best",
+            "mutual",
+            "cfs",
+            "fcbf",
+            "iwss",
+        ]:
             raise ValueError(
-                "splitter must be in {random, best, mutual, cfs, fcbf} got "
-                f"({feature_select})"
+                "splitter must be in {random, best, mutual, cfs, fcbf, iwss} "
+                f"got ({feature_select})"
             )
         self.criterion_function = getattr(self, f"_{self._criterion}")
         self.decision_criteria = getattr(self, f"_{self._criteria}")
@@ -409,6 +416,31 @@ class Splitter:
         mufs = MUFS(max_features=max_features, discrete=False)
         return mufs.fcbf(dataset, labels, 5e-4).get_results()
 
+    @staticmethod
+    def _fs_iwss(
+        dataset: np.array, labels: np.array, max_features: int
+    ) -> tuple:
+        """Correlattion-based feature selection based on iwss with max_features
+        limit
+
+        Parameters
+        ----------
+        dataset : np.array
+            array of samples
+        labels : np.array
+            labels of the dataset
+        max_features : int
+            number of features of the subspace
+            (< number of features in dataset)
+
+        Returns
+        -------
+        tuple
+            indices of the features selected
+        """
+        mufs = MUFS(max_features=max_features, discrete=False)
+        return mufs.iwss(dataset, labels, 0.25).get_results()
+
     def partition_impurity(self, y: np.array) -> np.array:
         return self.criterion_function(y)
 

stree/tests/Splitter_test.py

@@ -285,3 +285,15 @@ class Splitter_test(unittest.TestCase):
             Xs, computed = tcl.get_subspace(X, y, rs)
             self.assertListEqual(expected, list(computed))
             self.assertListEqual(X[:, expected].tolist(), Xs.tolist())
+
+    def test_get_iwss_subspaces(self):
+        results = [
+            (4, [1, 5, 9, 12]),
+            (6, [1, 5, 9, 12, 4, 15]),
+        ]
+        for rs, expected in results:
+            X, y = load_dataset(n_features=20, n_informative=7)
+            tcl = self.build(feature_select="iwss", random_state=rs)
+            Xs, computed = tcl.get_subspace(X, y, rs)
+            self.assertListEqual(expected, list(computed))
+            self.assertListEqual(X[:, expected].tolist(), Xs.tolist())