Handle fit kwargs in KElbowVisualizer quick method

yellowbrick/cluster/elbow.py

@@ -28,7 +28,7 @@
 from sklearn.preprocessing import LabelEncoder
 from sklearn.metrics.pairwise import pairwise_distances
 
-from yellowbrick.utils import KneeLocator
+from yellowbrick.utils import KneeLocator, get_param_names
 from yellowbrick.style.palettes import LINE_COLOR
 from yellowbrick.cluster.base import ClusteringScoreVisualizer
 from yellowbrick.exceptions import YellowbrickValueError, YellowbrickWarning
@@ -487,6 +487,15 @@ def kelbow_visualizer(
     viz : KElbowVisualizer
         The kelbow visualizer, fitted and finalized.
     """
+    klass = type(model)
+
+    # figure out which kwargs correspond to fit method
+    fit_params = get_param_names(klass.fit)
+
+    fit_kwargs = {
+        key: kwargs.pop(key) for key in fit_params if key in kwargs
+    }
+
     oz = KElbow(
         model,
         ax=ax,
@@ -496,7 +505,7 @@ def kelbow_visualizer(
         locate_elbow=locate_elbow,
         **kwargs
     )
-    oz.fit(X, y)
+    oz.fit(X, y, **fit_kwargs)
 
     if show:
         oz.show()

yellowbrick/utils/helpers.py

@@ -19,6 +19,7 @@
 ##########################################################################
 
 import re
+import inspect
 import sklearn
 import numpy as np
 
@@ -185,6 +186,28 @@ def is_monotonic(a, increasing=True):
     return np.all(a[1:] <= a[:-1], axis=0)
 
 
+def get_param_names(method):
+    """
+    Returns a list of keyword-only parameter names that may be
+    passed into method.
+
+    Parameters
+    ----------
+    method : function
+        The method for which to return keyword-only parameters.
+
+    Returns
+    -------
+    parameters : list
+        A list of keyword-only parameter names for method.
+    """
+    signature = inspect.signature(method)
+    parameters = [p for p in signature.parameters.values()
+                    if p.name != 'self' and p.kind != p.VAR_KEYWORD]
+
+    return sorted([p.name for p in parameters])
+
+
 ##########################################################################
 ## Numeric Computations
 ##########################################################################