How to fix ValueError: multiclass format is not supported
How to fix ValueError: multiclass format is not supported
这是我的代码，我尝试计算 ROC 分数，但我遇到了 ValueError 问题：不支持多类格式。我已经在寻找 sci-kit learn 但它没有帮助。最后，我仍然有 ValueError: multiclass format is not supported.
这是我的代码
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.metrics import confusion_matrix,zero_one_loss
from sklearn.metrics import classification_report,matthews_corrcoef,accuracy_score
from sklearn.metrics import roc_auc_score, auc
dtc = DecisionTreeClassifier()
bc = BaggingClassifier(base_estimator=dtc, n_estimators=10, random_state=17)
bc.fit(train_x, train_Y)
pred_y = bc.predict(test_x)
fprate, tprate, thresholds = roc_curve(test_Y, pred_y)
results = confusion_matrix(test_Y, pred_y)
error = zero_one_loss(test_Y, pred_y)
roc_auc_score(test_Y, pred_y)
FP = results.sum(axis=0) - np.diag(results)
FN = results.sum(axis=1) - np.diag(results)
TP = np.diag(results)
TN = results.sum() - (FP + FN + TP)
print('\n Time Processing: \n',time.process_time())
print('\n Confussion Matrix: \n', results)
print('\n Zero-one classification loss: \n', error)
print('\n True Positive: \n', TP)
print('\n True Negative: \n', TN)
print('\n False Positive: \n', FP)
print('\n False Negative: \n', FN)
print ('\n The Classification report:\n',classification_report(test_Y,pred_y, digits=6))
print ('MCC:', matthews_corrcoef(test_Y,pred_y))
print ('Accuracy:', accuracy_score(test_Y,pred_y))
print (auc(fprate, tprate))
print ('ROC Score:', roc_auc_score(test_Y,pred_y))
这是回溯
来自文档，roc_curve："Note: this implementation is restricted to the binary classification task."
您的标签 类 (y) 是 1 还是 0？如果没有，我认为您必须将 pos_label 参数添加到 roc_curve 调用中。
fprate, tprate, thresholds = roc_curve(test_Y, pred_y, pos_label='your_label')
或：
test_Y = your_test_y_array # these are either 1's or 0's
fprate, tprate, thresholds = roc_curve(test_Y, pred_y)
pos_label设置为1，否则会报错
fprate, tprate, thresholds = roc_curve(test_Y, pred_y, pos_label=1)
这是我的代码，我尝试计算 ROC 分数，但我遇到了 ValueError 问题：不支持多类格式。我已经在寻找 sci-kit learn 但它没有帮助。最后，我仍然有 ValueError: multiclass format is not supported.
这是我的代码
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.metrics import confusion_matrix,zero_one_loss
from sklearn.metrics import classification_report,matthews_corrcoef,accuracy_score
from sklearn.metrics import roc_auc_score, auc
dtc = DecisionTreeClassifier()
bc = BaggingClassifier(base_estimator=dtc, n_estimators=10, random_state=17)
bc.fit(train_x, train_Y)
pred_y = bc.predict(test_x)
fprate, tprate, thresholds = roc_curve(test_Y, pred_y)
results = confusion_matrix(test_Y, pred_y)
error = zero_one_loss(test_Y, pred_y)
roc_auc_score(test_Y, pred_y)
FP = results.sum(axis=0) - np.diag(results)
FN = results.sum(axis=1) - np.diag(results)
TP = np.diag(results)
TN = results.sum() - (FP + FN + TP)
print('\n Time Processing: \n',time.process_time())
print('\n Confussion Matrix: \n', results)
print('\n Zero-one classification loss: \n', error)
print('\n True Positive: \n', TP)
print('\n True Negative: \n', TN)
print('\n False Positive: \n', FP)
print('\n False Negative: \n', FN)
print ('\n The Classification report:\n',classification_report(test_Y,pred_y, digits=6))
print ('MCC:', matthews_corrcoef(test_Y,pred_y))
print ('Accuracy:', accuracy_score(test_Y,pred_y))
print (auc(fprate, tprate))
print ('ROC Score:', roc_auc_score(test_Y,pred_y))
这是回溯
来自文档，roc_curve："Note: this implementation is restricted to the binary classification task."
您的标签 类 (y) 是 1 还是 0？如果没有，我认为您必须将 pos_label 参数添加到 roc_curve 调用中。
fprate, tprate, thresholds = roc_curve(test_Y, pred_y, pos_label='your_label')
或：
test_Y = your_test_y_array # these are either 1's or 0's
fprate, tprate, thresholds = roc_curve(test_Y, pred_y)
pos_label设置为1，否则会报错
fprate, tprate, thresholds = roc_curve(test_Y, pred_y, pos_label=1)