Resurrected PR from
@@ -553,6 +553,21 @@ class SVC(BaseSVC):
intercept_ : array, shape = [n_class * (n_class-1) / 2]
Constants in decision function.
+ fit_status_ : int
+ 0 if correctly fitted, 1 otherwise (will raise warning)
+
+ probA_ : array, shape = [n_class * (n_class-1) / 2]
+ probB_ : array, shape = [n_class * (n_class-1) / 2]
+ If probability=True, the parameters learned in Platt scaling to
+ produce probability estimates from decision values. If
+ probability=False, an empty array. Platt scaling uses the logistic
+ function
+ ``1 / (1 + exp(decision_value * probA_ + probB_))``
+ where ``probA_`` and ``probB_`` are learned from the dataset. For more
+ information on the multiclass case and training procedure see section
+ 8 of LIBSVM: A Library for Support Vector Machines (in References)
+ for more.
+
Examples
--------
>>> import numpy as np
@@ -578,6 +593,11 @@ class SVC(BaseSVC):
implemented using liblinear. Check the See also section of
LinearSVC for more comparison element.
+ Notes
+ -----
+ **References:**
+ `LIBSVM: A Library for Support Vector Machines
+ <http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf>`__
"""
_impl = 'c_svc'
@@ -740,6 +760,12 @@ class NuSVC(BaseSVC):
LinearSVC
Scalable linear Support Vector Machine for classification using
liblinear.
+
+ Notes
+ -----
+ **References:**
+ `LIBSVM: A Library for Support Vector Machines
+ <http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf>`__
"""
_impl = 'nu_svc'
@@ -863,6 +889,12 @@ class SVR(BaseLibSVM, RegressorMixin):
LinearSVR
Scalable Linear Support Vector Machine for regression
implemented using liblinear.
+
+ Notes
+ -----
+ **References:**
+ `LIBSVM: A Library for Support Vector Machines
+ <http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf>`__
"""
_impl = 'epsilon_svr'
@@ -984,6 +1016,12 @@ class NuSVR(BaseLibSVM, RegressorMixin):
SVR
epsilon Support Vector Machine for regression implemented with libsvm.
+
+ Notes
+ -----
+ **References:**
+ `LIBSVM: A Library for Support Vector Machines
+ <http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf>`__
"""
_impl = 'nu_svr'
