如何知道多少是0类，多少是1类？

Question

我有一个代码可以让我获得 SVM 的准确性，但我想知道 0 类和 1 类分别是多少。

这是代码

from sklearn.svm import SVC

from sklearn.metrics import accuracy_score

clf = SVC(C=10000.0, kernel='rbf')

t0 = time()

clf.fit(features_train, labels_train)

print "training_time:", round(time()-t0, 3), "s"

t0 = time()

pred = clf.predict(features_test)

print "prediction time:", round(time()-t0, 3), "s"

acc = accuracy_score(pred, labels_test)

print acc

我已经尝试过下面的代码，但没有成功......

from sklearn.svm import SVC

from sklearn.metrics import accuracy_score

clf = SVC(C=10000.0, kernel='rbf', probability=True)

t0 = time()

clf.fit(features_train, labels_train)

print "training_time:", round(time()-t0, 3), "s"

t0 = time()

pred = clf.predict(features_test)

class = clf.predict_proba(features_test)

print sum(class)

print "prediction time:", round(time()-t0, 3), "s"

acc = accuracy_score(pred, labels_test)

print acc

我错过了什么？泰！

Answer 1

您可以创建混淆矩阵来了解您的预测from sklearn.metrics import confusion_matrixconfusion_matrix(labels_test, pred)