[FIX] Fix prediction workflow with one cascade layer

CHANGELOG.rst

@@ -30,6 +30,7 @@ Version 0.1.*
 .. |Fix| replace:: :raw-html:`<span class="badge badge-danger">Fix</span>` :raw-latex:`{\small\sc [Fix]}`
 .. |API| replace:: :raw-html:`<span class="badge badge-warning">API Change</span>` :raw-latex:`{\small\sc [API Change]}`
 
+- |Fix| fix the prediction workflow with only one cascade layer (`#56 <https://github.com/LAMDA-NJU/Deep-Forest/pull/56>`__) @xuyxu
 - |Fix| fix inconsistency on predictor name (`#52 <https://github.com/LAMDA-NJU/Deep-Forest/pull/52>`__) @xuyxu
 - |Feature| add official support for ManyLinux-aarch64 (`#47 <https://github.com/LAMDA-NJU/Deep-Forest/pull/47>`__) @xuyxu
 - |Fix| fix accepted types of target for :obj:`CascadeForestRegressor` (`#44 <https://github.com/LAMDA-NJU/Deep-Forest/pull/44>`__) @xuyxu

deepforest/_layer.py

@@ -134,24 +134,8 @@ def _validate_params(self):
             raise ValueError(msg.format(self.n_trees))
 
     def transform(self, X):
-        """
-        Return the concatenated transformation results from all base
-        estimators."""
-        n_samples, _ = X.shape
-        X_aug = np.zeros((n_samples, self.n_outputs * self.n_estimators))
-        for idx, (key, estimator) in enumerate(self.estimators_.items()):
-            if self.verbose > 1:
-                msg = "{} - Evaluating estimator = {:<5} in layer = {}"
-                key = key.split("-")[-1] + "_" + str(key.split("-")[-2])
-                print(msg.format(_utils.ctime(), key, self.layer_idx))
-            if self.partial_mode:
-                # Load the estimator from the buffer
-                estimator = self.buffer.load_estimator(estimator)
-
-            left, right = self.n_outputs * idx, self.n_outputs * (idx + 1)
-            X_aug[:, left:right] += estimator.predict(X)
-
-        return X_aug
+        """Preserved for the naming consistency."""
+        return self.predict_full(X)
 
     def predict_full(self, X):
         """Return the concatenated predictions from all base estimators."""

deepforest/cascade.py

@@ -1334,8 +1334,12 @@ def predict_proba(self, X):
             predictor = self.buffer_.load_predictor(self.predictor_)
             proba = predictor.predict_proba(X_middle_test_)
         else:
-            proba = layer.predict_full(X_middle_test_)
-            proba = _utils.merge_proba(proba, self.n_outputs_)
+            if self.n_layers_ > 1:
+                proba = layer.predict_full(X_middle_test_)
+                proba = _utils.merge_proba(proba, self.n_outputs_)
+            else:
+                # Directly merge results with one cascade layer only
+                proba = _utils.merge_proba(X_aug_test_, self.n_outputs_)
 
         return proba
 
@@ -1512,6 +1516,11 @@ def predict(self, X):
             predictor = self.buffer_.load_predictor(self.predictor_)
             _y = predictor.predict(X_middle_test_)
         else:
-            _y = layer.predict_full(X_middle_test_)
-            _y = _utils.merge_proba(_y, self.n_outputs_)
+            if self.n_layers_ > 1:
+                _y = layer.predict_full(X_middle_test_)
+                _y = _utils.merge_proba(_y, self.n_outputs_)
+            else:
+                # Directly merge results with one cascade layer only
+                _y = _utils.merge_proba(X_aug_test_, self.n_outputs_)
+
         return _y