Python sklearn SVC.fit() got error -

Python sklearn SVC.fit() got error -

my former version of sklearn 0.13 , update 0.14.1. , code below doesn't work now(it worked before updating). know reason? here code , result.

print 'reading train data...' dataset=genfromtxt(open(r'data/train.csv','r'),delimiter=',',dtype=int,skip_header=1) train_data=[i[1:] in dataset] label=[i[0] in dataset] print 'training...' clf=svm.svc(kernel='poly',degree=9) clf.fit(train_data,label) pickle.dump(clf,open(model,'w'))

and here result:

reading train data... training... traceback (most recent phone call last): file "svm_train.py", line 35, in <module> main() file "svm_train.py", line 23, in main clf.fit(train_data,label) file "d:\anaconda\lib\site-packages\sklearn\svm\base.py", line 178, in fit fit(x, y, sample_weight, solver_type, kernel, random_seed=seed) file "d:\anaconda\lib\site-packages\sklearn\svm\base.py", line 233, in _dense_fit max_iter=self.max_iter, random_seed=random_seed) file "libsvm.pyx", line 53, in sklearn.svm.libsvm.fit (sklearn\svm\libsvm.c:1388) typeerror: fit() got unexpected keyword argument 'random_seed'

also, python environment anaconda python.

python error-handling scikit-learn svm