我正在尝试使用ibm的aif360库进行借记。 我正在研究一个线性回归模型,想尝试一个指标来计算特权群体和非特权群体之间的差异。 但是,当运行此代码时,我会出现以下错误:
TypeError:difference()缺少1个必需的位置参数:“metric\u fun”
我已经研究了这个函数的类,但它们指的是一个度量值,也阅读了文档,但没有进一步的了解。 函数缺少一个参数,但我不知道它需要哪个参数
代码的一小部分是:
train_pp_bld = StructuredDataset(df=pd.concat((x_train, y_train),
axis=1),
label_names=['decile_score'],
protected_attribute_names=['sex_Male'],
privileged_protected_attributes=1,
unprivileged_protected_attributes=0)
privileged_groups = [{'sex_Male': 1}]
unprivileged_groups = [{'sex_Male': 0}]
# Create the metric object
metric_train_bld = DatasetMetric(train_pp_bld,
unprivileged_groups=unprivileged_groups,
privileged_groups=privileged_groups)
# Metric for the original dataset
metric_orig_train = DatasetMetric(train_pp_bld,
unprivileged_groups=unprivileged_groups,
privileged_groups=privileged_groups)
display(Markdown("#### Original training dataset"))
print("Difference in mean outcomes between unprivileged and privileged groups = %f" % metric_orig_train.difference())
给出的堆栈跟踪是:
Traceback (most recent call last):
File "/Users/sef/Desktop/Thesis/Python Projects/Stats/COMPAS_Debias_AIF360_Continuous_Variable.py", line 116, in <module>
print("Difference in mean outcomes between unprivileged and privileged groups = %f" % metric_orig_train.difference())
File "/Users/sef/opt/anaconda3/envs/AI/lib/python3.8/site-packages/aif360/metrics/metric.py", line 37, in wrapper
result = func(*args, **kwargs)
TypeError: difference() missing 1 required positional argument: 'metric_fun'
创建函数后:
def privileged_value(self, privileged=False):
if privileged:
return unprivileged_groups['sex_Male']
else:
return privileged_groups['sex_Male']
display(Markdown("#### Original training dataset"))
print("Difference in mean outcomes between unprivileged and privileged groups = %f" % metric_orig_train.difference(privileged_value))
仍然会得到类似的错误回溯:
Traceback (most recent call last):
File "/Users/sef/Desktop/Thesis/Python Projects/Stats/COMPAS_Debias_AIF360_Continuous_Variable.py", line 123, in <module>
print("Difference in mean outcomes between unprivileged and privileged groups = %f" % metric_orig_train.difference(privileged_value))
File "/Users/sef/opt/anaconda3/envs/AI/lib/python3.8/site-packages/aif360/metrics/metric.py", line 37, in wrapper
result = func(*args, **kwargs)
File "/Users/sef/opt/anaconda3/envs/AI/lib/python3.8/site-packages/aif360/metrics/dataset_metric.py", line 77, in difference
return metric_fun(privileged=False) - metric_fun(privileged=True)
File "/Users/youssefennali/Desktop/Thesis/Python Projects/Stats/COMPAS_Debias_AIF360_Continuous_Variable.py", line 120, in privileged_value
return privileged_groups['sex_Male']
TypeError: list indices must be integers or slices, not str
有人能给我指一下正确的方向吗? 网上没有类似代码的示例
问候,
海基会
嗯,在不知道您正在使用的库的任何信息的情况下,错误消息似乎仍然非常清楚,特别是因为您只调用了
difference
一次,如下所示:错误消息告诉您应该在此调用中传递参数。参数的名称是
metric_fun
,这向我建议您应该向它传递一个函数引用注意:可能是在代码外部调用了difference()。当您提供错误消息时,请始终提交随附的堆栈跟踪(如果有)。然后,我们可以确切地看到问题发生在代码中的什么地方
查看GitHub上库的源代码,需要将对函数的引用传递到
difference(self, metric_fun)
。所有的区别就是用privileged=False
作为输入的函数的输出减去privileged=True
作为输入的函数的输出创建一个这样的函数,并将其传递到差异中
相关问题 更多 >
编程相关推荐