Add max_features to MFS to help STree integration

mfs/Selection.py

@@ -109,10 +109,16 @@ class MFS:
 
     Correlated Feature Selection as in "Correlation-based Feature Selection for
     Machine Learning" by Mark A. Hall
+
+    Parameters
+    ----------
+    max_features: int
+        The maximum number of features to return
     """
 
-    def __init__(self):
+    def __init__(self, max_features):
         self._initialize()
+        self._max_features = max_features
 
     def _initialize(self):
         """Initialize the attributes so support multiple calls using same
@@ -180,8 +186,8 @@ class MFS:
         """
         # lgtm has already recognized that this is a false positive
         rcf = self._su_labels[
-            features
-        ].sum()  # lgtm [py/hash-unhashable-value]
+            features  # lgtm [py/hash-unhashable-value]
+        ].sum()
         rff = 0.0
         k = len(features)
         for pair in list(combinations(features, 2)):
@@ -229,7 +235,10 @@ class MFS:
             candidates.append(feature_order[id_selected])
             self._scores.append(merit)
             del feature_order[id_selected]
-            if len(feature_order) == 0:
+            if (
+                len(feature_order) == 0
+                or len(candidates) == self._max_features
+            ):
                 # Force leaving the loop
                 continue_condition = False
             if len(self._scores) >= 5:
@@ -253,7 +262,7 @@ class MFS:
         self._result = candidates
         return self
 
-    def fcbs(self, X, y, threshold):
+    def fcbf(self, X, y, threshold):
         """Fast Correlation-Based Filter
 
         Parameters
@@ -273,10 +282,10 @@ class MFS:
         Raises
         ------
         ValueError
-            if the threshold is less than a selected value of 1e-4
+            if the threshold is less than a selected value of 1e-7
         """
-        if threshold < 1e-4:
-            raise ValueError("Threshold cannot be less than 1e-4")
+        if threshold < 1e-7:
+            raise ValueError("Threshold cannot be less than 1e-7")
         self._initialize()
         self.X_ = X
         self.y_ = y
@@ -301,6 +310,8 @@ class MFS:
                     s_list[index_q] = 0.0
             self._result.append(index_p)
             self._scores.append(s_list[index_p])
+            if len(self._result) == self._max_features:
+                break
         return self
 
     def get_results(self):

mfs/tests/MFS_test.py

@@ -21,8 +21,8 @@ class MFS_test(unittest.TestCase):
             self.assertAlmostEqual(a, b, tol)
 
     def test_initialize(self):
-        mfs = MFS()
-        mfs.fcbs(self.X_w, self.y_w, 0.05)
+        mfs = MFS(max_features=100)
+        mfs.fcbf(self.X_w, self.y_w, 0.05)
         mfs._initialize()
         self.assertIsNone(mfs.get_results())
         self.assertListEqual([], mfs.get_scores())
@@ -30,7 +30,7 @@ class MFS_test(unittest.TestCase):
         self.assertIsNone(mfs._su_labels)
 
     def test_csf_wine(self):
-        mfs = MFS()
+        mfs = MFS(max_features=100)
         expected = [6, 12, 9, 4, 10, 0]
         self.assertListAlmostEqual(
             expected, mfs.cfs(self.X_w, self.y_w).get_results()
@@ -45,8 +45,21 @@ class MFS_test(unittest.TestCase):
         ]
         self.assertListAlmostEqual(expected, mfs.get_scores())
 
+    def test_csf_max_features(self):
+        mfs = MFS(max_features=3)
+        expected = [6, 12, 9]
+        self.assertListAlmostEqual(
+            expected, mfs.cfs(self.X_w, self.y_w).get_results()
+        )
+        expected = [
+            0.5218299405215557,
+            0.602513857132804,
+            0.4877384978817362,
+        ]
+        self.assertListAlmostEqual(expected, mfs.get_scores())
+
     def test_csf_iris(self):
-        mfs = MFS()
+        mfs = MFS(max_features=100)
         expected = [3, 2, 0, 1]
         computed = mfs.cfs(self.X_i, self.y_i).get_results()
         self.assertListAlmostEqual(expected, computed)
@@ -58,9 +71,9 @@ class MFS_test(unittest.TestCase):
         ]
         self.assertListAlmostEqual(expected, mfs.get_scores())
 
-    def test_fcbs_wine(self):
-        mfs = MFS()
-        computed = mfs.fcbs(self.X_w, self.y_w, threshold=0.05).get_results()
+    def test_fcbf_wine(self):
+        mfs = MFS(max_features=100)
+        computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.05).get_results()
         expected = [6, 9, 12, 0, 11, 4]
         self.assertListAlmostEqual(expected, computed)
         expected = [
@@ -73,30 +86,42 @@ class MFS_test(unittest.TestCase):
         ]
         self.assertListAlmostEqual(expected, mfs.get_scores())
 
-    def test_fcbs_iris(self):
-        mfs = MFS()
-        computed = mfs.fcbs(self.X_i, self.y_i, threshold=0.05).get_results()
-        expected = [3, 2]
-        self.assertListAlmostEqual(expected, computed)
-        expected = [0.870521418179061, 0.810724587460511]
-        self.assertListAlmostEqual(expected, mfs.get_scores())
-
-    def test_compute_su_labels(self):
-        mfs = MFS()
-        mfs.fcbs(self.X_i, self.y_i, threshold=0.05)
-        expected = [0.0, 0.0, 0.810724587460511, 0.870521418179061]
-        self.assertListAlmostEqual(expected, mfs._compute_su_labels().tolist())
-        mfs._su_labels = [1, 2, 3, 4]
-        self.assertListAlmostEqual([1, 2, 3, 4], mfs._compute_su_labels())
-
-    def test_invalid_threshold(self):
-        mfs = MFS()
-        with self.assertRaises(ValueError):
-            mfs.fcbs(self.X_i, self.y_i, threshold=1e-5)
-
-    def test_fcbs_exit_threshold(self):
-        mfs = MFS()
-        computed = mfs.fcbs(self.X_w, self.y_w, threshold=0.4).get_results()
+    def test_fcbf_max_features(self):
+        mfs = MFS(max_features=3)
+        computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.05).get_results()
+        expected = [6, 9, 12]
+        self.assertListAlmostEqual(expected, computed)
+        expected = [
+            0.5218299405215557,
+            0.46224298637417455,
+            0.44518278979085646,
+        ]
+        self.assertListAlmostEqual(expected, mfs.get_scores())
+
+    def test_fcbf_iris(self):
+        mfs = MFS(max_features=100)
+        computed = mfs.fcbf(self.X_i, self.y_i, threshold=0.05).get_results()
+        expected = [3, 2]
+        self.assertListAlmostEqual(expected, computed)
+        expected = [0.870521418179061, 0.810724587460511]
+        self.assertListAlmostEqual(expected, mfs.get_scores())
+
+    def test_compute_su_labels(self):
+        mfs = MFS(max_features=100)
+        mfs.fcbf(self.X_i, self.y_i, threshold=0.05)
+        expected = [0.0, 0.0, 0.810724587460511, 0.870521418179061]
+        self.assertListAlmostEqual(expected, mfs._compute_su_labels().tolist())
+        mfs._su_labels = [1, 2, 3, 4]
+        self.assertListAlmostEqual([1, 2, 3, 4], mfs._compute_su_labels())
+
+    def test_invalid_threshold(self):
+        mfs = MFS(max_features=100)
+        with self.assertRaises(ValueError):
+            mfs.fcbf(self.X_i, self.y_i, threshold=1e-15)
+
+    def test_fcbf_exit_threshold(self):
+        mfs = MFS(max_features=100)
+        computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.4).get_results()
         expected = [6, 9, 12]
         self.assertListAlmostEqual(expected, computed)
         expected = [