Merge pull request scikit-learn#5966 from hlin117/pairwise-docs

[Needs Review] Added information about gamma parameter for pairwise kernels

Author: agramfort

sklearn/metrics/pairwise.py

@@ -730,10 +730,13 @@ def polynomial_kernel(X, Y=None, degree=3, gamma=None, coef0=1):
 
     Y : ndarray of shape (n_samples_2, n_features)
 
-    coef0 : int, default 1
-
     degree : int, default 3
 
+    gamma : float, default None
+        if None, defaults to 1.0 / n_samples_1
+
+    coef0 : int, default 1
+
     Returns
     -------
     Gram matrix : array of shape (n_samples_1, n_samples_2)
@@ -763,6 +766,9 @@ def sigmoid_kernel(X, Y=None, gamma=None, coef0=1):
 
     Y : ndarray of shape (n_samples_2, n_features)
 
+    gamma : float, default None
+        If None, defaults to 1.0 / n_samples_1
+
     coef0 : int, default 1
 
     Returns
@@ -796,7 +802,8 @@ def rbf_kernel(X, Y=None, gamma=None):
 
     Y : array of shape (n_samples_Y, n_features)
 
-    gamma : float
+    gamma : float, default None
+        If None, defaults to 1.0 / n_samples_X
 
     Returns
     -------
@@ -827,8 +834,11 @@ def laplacian_kernel(X, Y=None, gamma=None):
     Parameters
     ----------
     X : array of shape (n_samples_X, n_features)
+
     Y : array of shape (n_samples_Y, n_features)
-    gamma : float
+
+    gamma : float, default None
+        If None, defaults to 1.0 / n_samples_X
 
     Returns
     -------