DOC svm add callable as accepted type for kernel parameter
@@ -538,10 +538,9 @@ class SVC(BaseSVC):
inversely proportional to C. Must be strictly positive. The penalty
is a squared l2 penalty.
- kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'}, default='rbf'
+ kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'} or callable, \
+ default='rbf'
Specifies the kernel type to be used in the algorithm.
- It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or
- a callable.
If none is given, 'rbf' will be used. If a callable is given it is
used to pre-compute the kernel matrix from data matrices; that matrix
should be an array of shape ``(n_samples, n_samples)``.
@@ -802,10 +801,9 @@ class NuSVC(BaseSVC):
<nu_svc>`) and a lower bound of the fraction of support vectors.
Should be in the interval (0, 1].
- kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'}, default='rbf'
+ kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'} or callable, \
+ default='rbf'
Specifies the kernel type to be used in the algorithm.
- It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or
- a callable.
If none is given, 'rbf' will be used. If a callable is given it is
used to precompute the kernel matrix.
@@ -1067,10 +1065,9 @@ class SVR(RegressorMixin, BaseLibSVM):
Parameters
----------
- kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'}, default='rbf'
+ kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'} or callable, \
+ default='rbf'
Specifies the kernel type to be used in the algorithm.
- It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or
- a callable.
If none is given, 'rbf' will be used. If a callable is given it is
used to precompute the kernel matrix.
@@ -1271,10 +1268,9 @@ class NuSVR(RegressorMixin, BaseLibSVM):
C : float, default=1.0
Penalty parameter C of the error term.
- kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'}, default='rbf'
+ kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'} or callable, \
+ default='rbf'
Specifies the kernel type to be used in the algorithm.
- It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or
- a callable.
If none is given, 'rbf' will be used. If a callable is given it is
used to precompute the kernel matrix.
@@ -1454,10 +1450,9 @@ class OneClassSVM(OutlierMixin, BaseLibSVM):
Parameters
----------
- kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'}, default='rbf'
+ kernel : {'linear', 'poly', 'rbf', 'sigmoid', 'precomputed'} or callable, \
+ default='rbf'
Specifies the kernel type to be used in the algorithm.
- It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or
- a callable.
If none is given, 'rbf' will be used. If a callable is given it is
used to precompute the kernel matrix.
