Enforce partial_fit taking an optional y.

amueller · amueller · commit 663204369875 · 2015-01-28T10:49:08.000-05:00
diff --git a/doc/whats_new.rst b/doc/whats_new.rst
@@ -173,8 +173,8 @@ Enhancements
    - Parallelized calculation of :func:`pairwise_distances` is now supported
      for scipy metrics and custom callables. By `Joel Nothman`_.
 
-   - Allow the use of all clustering algorithms in :class:`pipeline.Pipeline`.
-     By `Andreas Müller`_.
+   - Allow the fitting and scoring of all clustering algorithms in
+     :class:`pipeline.Pipeline`. By `Andreas Müller`_.
 
 Documentation improvements
 ..........................
diff --git a/sklearn/decomposition/incremental_pca.py b/sklearn/decomposition/incremental_pca.py
@@ -174,7 +174,7 @@ def fit(self, X, y=None):
             self.partial_fit(X[batch])
         return self
 
-    def partial_fit(self, X):
+    def partial_fit(self, X, y=None):
         """Incremental fit with X. All of X is processed as a single batch.
 
         Parameters
diff --git a/sklearn/neural_network/rbm.py b/sklearn/neural_network/rbm.py
@@ -217,7 +217,7 @@ def gibbs(self, v):
 
         return v_
 
-    def partial_fit(self, X):
+    def partial_fit(self, X, y=None):
         """Fit the model to the data X which should contain a partial
         segment of the data.
 
@@ -301,7 +301,7 @@ def score_samples(self, X):
         returns the log of the logistic function of the difference.
         """
         check_is_fitted(self, "components_")
-        
+
         v = check_array(X, accept_sparse='csr')
         rng = check_random_state(self.random_state)
 
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
@@ -253,7 +253,7 @@ def check_fit_score_takes_y(name, Estimator):
     estimator = Estimator()
     set_fast_parameters(estimator)
     set_random_state(estimator)
-    funcs = ["fit", "score"]
+    funcs = ["fit", "score", "partial_fit"]
 
     for func_name in funcs:
         func = getattr(estimator, func_name, None)
