DOC expand FunctionTransform docstring

larsmans · amueller · commit bf8b91f9103f · 2015-08-03T11:45:16.000-04:00
diff --git a/sklearn/preprocessing/function_transformer.py b/sklearn/preprocessing/function_transformer.py
@@ -11,6 +11,13 @@ def _identity(X):
 class FunctionTransformer(BaseEstimator, TransformerMixin):
     """Constructs a transformer from an arbitrary callable.
 
+    A FunctionTransformer forwards its X (and optionally y) arguments to a
+    user-defined function or function object and returns the result of this
+    function. This is useful for stateless transformations such as taking the
+    log of frequencies, doing custom scaling, etc.
+
+    A FunctionTransformer will not do any checks on its function's output.
+
     Note: If a lambda is used as the function, then the resulting
     transformer will not be pickleable.
 
@@ -24,9 +31,14 @@ class FunctionTransformer(BaseEstimator, TransformerMixin):
     validate : bool, optional default=True
         Indicate that the input X array should be checked before calling
         func. If validate is false, there will be no input validation.
+        If it is true, then X will be converted to a 2-dimensional NumPy
+        array or sparse matrix. If this conversion is not possible or X
+        contains NaN or infinity, an exception is raised.
 
     accept_sparse : boolean, optional
-        Indicate that func accepts a sparse matrix as input.
+        Indicate that func accepts a sparse matrix as input. If validate is
+        False, this has no effect. Otherwise, if accept_sparse is false,
+        sparse matrix inputs will cause an exception to be raised.
 
     pass_y: bool, optional default=False
         Indicate that transform should forward the y argument to the
