from sklearn import svm, metrics
data = [[0, 0], [1, 0], [0, 1], [1, 1]]
labels = [0, 1, 1, 0]
examples = [[0, 0], [1, 0]]
examples_label = [0, 1]

clf = svm.SVC()
clf.fit(data, labels)
results = clf.predict(examples)
print(results)

score = metrics.accuracy_score(examples_label, results)
print("정답률:", score)
