from skrvm import RVC

from sklearn.model_selection import cross_val_score

from sklearn.model_selection import train_test_split

def load_data():

return data_set, label_set

data, label = load_data()

X_train,X_test,y_train,y_test = train_test_split(data,label,test_size=0.3,random_state=0)

clf = RVC()

# clf.fit(rvm_data, rvm_target)

# print(clf.score(rvm_data, rvm_target))

clf.fit(X_train, y_train)

scoring = 'accuracy'

scores = cross_val_score(clf,X_test, y_test, cv=7)

print(scores.mean())