您可以按降序对概率进行排序并检索前 n 个.要计算准确度，您可以定义自定义函数，如果您的 y_true 属于 top-n，则该函数将认为预测是正确的.沿着这些路线的东西应该可以工作:

You can sort your probabilities in descending order and retrieve the top-n. To calculate accuracy, you can define your custom function that will consider a prediction to be correct if your y_true belongs in top-n. Something along these lines should work:

probs = clf.predict_proba(X_test)
# Sort desc and only extract the top-n
top_n = np.argsort(probs)[:,:-n-1:-1]

# Calculate accuracy
true_preds = 0
for i in range(len(y_test)):
    if y_test[i] in top_n[i]:
        true_preds += 1

accuracy = true_preds/len(y_test)