如何使用Shap（Shapley添加说明）来解释用户提供的功能？

发布于 2025-01-18 18:53:25 字数 1317 浏览 2 评论 0原文

我想使用Python Shap模块来解释用户提供的非线性功能。我将以一个简单的例子作为代表，但不能成功运行。我想询问是否可以将Shap用于此简单模型，以及是否可以实现它。

这是我的代码。

import numpy as np
import shap

def f(x):
        y = x[0] ** 2.5 + 3 * x[1] + 10
        return np.array(y)
x = np.arange(20).reshape((2, 10))

explainer = shap.Explainer(f)
shap_values = explainer(x)

以下是错误消息

Traceback (most recent call last):
  File "D:\Python\lib\code.py", line 90, in runcode
    exec(code, self.locals)
  File "<input>", line 1, in <module>
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_permutation.py", line 74, in __call__
    return super().__call__(
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_explainer.py", line 258, in __call__
    row_result = self.explain_row(
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_permutation.py", line 132, in explain_row
    outputs = fm(masks, zero_index=0, batch_size=batch_size)
  File "E:\PYCHARM\lib\site-packages\shap\utils\_masked_model.py", line 64, in __call__
    return self._full_masking_call(full_masks, zero_index=zero_index, batch_size=batch_size)
  File "E:\PYCHARM\lib\site-packages\shap\utils\_masked_model.py", line 93, in _full_masking_call
    masked_inputs = self.masker(mask, *self.args)
TypeError: 'NoneType' object is not callable

原文

I want to use the python Shap module to interpret user supplied nonlinear functions. I'll take just one simple example as a representative, but it cannot run successfully. I would like to ask if Shap can be used for this simple model and if yes how to implement it.

Here is my code.

import numpy as np
import shap

def f(x):
        y = x[0] ** 2.5 + 3 * x[1] + 10
        return np.array(y)
x = np.arange(20).reshape((2, 10))

explainer = shap.Explainer(f)
shap_values = explainer(x)

Below are the error messages

Traceback (most recent call last):
  File "D:\Python\lib\code.py", line 90, in runcode
    exec(code, self.locals)
  File "<input>", line 1, in <module>
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_permutation.py", line 74, in __call__
    return super().__call__(
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_explainer.py", line 258, in __call__
    row_result = self.explain_row(
  File "E:\PYCHARM\lib\site-packages\shap\explainers\_permutation.py", line 132, in explain_row
    outputs = fm(masks, zero_index=0, batch_size=batch_size)
  File "E:\PYCHARM\lib\site-packages\shap\utils\_masked_model.py", line 64, in __call__
    return self._full_masking_call(full_masks, zero_index=zero_index, batch_size=batch_size)
  File "E:\PYCHARM\lib\site-packages\shap\utils\_masked_model.py", line 93, in _full_masking_call
    masked_inputs = self.masker(mask, *self.args)
TypeError: 'NoneType' object is not callable

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肩上的翅膀 2025-01-25 18:53:25

您的意思是：10个数据点，2个功能，1个结果？

import numpy as np
from shap import KernelExplainer


def f(x):
    y = x[:, 0] ** 2.5 + 3 * x[:, 1] + 10
    return np.array(y)


x = np.arange(20).reshape((10,2))
explainer = KernelExplainer(f, x)
shap_values = explainer.shap_values(x)

Did you mean this: 10 datapoints, 2 features, 1 outcome?

import numpy as np
from shap import KernelExplainer


def f(x):
    y = x[:, 0] ** 2.5 + 3 * x[:, 1] + 10
    return np.array(y)


x = np.arange(20).reshape((10,2))
explainer = KernelExplainer(f, x)
shap_values = explainer.shap_values(x)

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