Python ValueError: 数据不是二进制的并且未指定 pos_label
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ValueError: Data is not binary and pos_label is not specified
提问by
I am trying to calculate roc_auc_score, but I am getting following error.
我正在尝试计算roc_auc_score，但出现以下错误。
"ValueError: Data is not binary and pos_label is not specified"
My code snippet is as follows:
我的代码片段如下：
import numpy as np
from sklearn.metrics import roc_auc_score
y_scores=np.array([ 0.63, 0.53, 0.36, 0.02, 0.70 ,1 , 0.48, 0.46, 0.57])
y_true=np.array(['0', '1', '0', '0', '1', '1', '1', '1', '1'])
roc_auc_score(y_true, y_scores)
Please tell me what is wrong with it.
请告诉我它有什么问题。
采纳答案by jabaldonedo
You only need to change y_trueso it looks like this:
你只需要改变y_true它看起来像这样：
y_true=np.array([0, 1, 0, 0, 1, 1, 1, 1, 1])
Explanation:If you take a look to what roc_auc_scorefunctions does in https://github.com/scikit-learn/scikit-learn/blob/0.15.X/sklearn/metrics/metrics.pyyou will see that y_trueis evaluated as follows:
说明：如果您查看https://github.com/scikit-learn/scikit-learn/blob/0.15.X/sklearn/metrics/metrics.py 中的roc_auc_score函数的作用，您将看到其评估如下：y_true
classes = np.unique(y_true)
if (pos_label is None and not (np.all(classes == [0, 1]) or
np.all(classes == [-1, 1]) or
np.all(classes == [0]) or
np.all(classes == [-1]) or
np.all(classes == [1]))):
raise ValueError("Data is not binary and pos_label is not specified")
At the moment of the execution pos_labelis None, but as long as your are defining y_trueas an array of characters the np.allare always falseand as all of them are negated then the if condition is trueand the exception is raised.
在执行的那一刻pos_labelis None，但只要您定义y_true为字符数组，np.allare alwaysfalse并且所有这些都被否定，则 if 条件为，true并引发异常。
回答by mAge
We have problem in
y_true=np.array(['0', '1', '0', '0', '1', '1', '1', '1', '1'])Convert values of y_true to Boolean
我们在y_true=np.array(['0', '1', '0', '0', '1', '1', '1', '1', '1'])将 y_true 的值转换为布尔值时遇到问题
y_true= '1' <= y_true
print(y_true) # [False True False False True True True True True]
