statsmodels 引發 TypeError：優化輸入中的輸入類型不支持 ufunc 'isfinite'

Question

我在運行我的代碼時需要幫助，它顯示錯誤：-“類型錯誤：輸入類型不支持 ufunc 'isfinite'，並且根據強制轉換規則“安全”，輸入無法安全地強制轉換為任何支持的類型"

我找到了幾個解決方案（ statsmodels raises TypeError: ufunc 'isfinite' not supported for the input types changed the datatype to float or int 仍然無法正常工作。誰能告訴我我在下面的代碼中做錯了什么：

import statsmodels.api as sm

X = np.append(arr = np.ones((50,1)).astype(int),values=X,axis=1)

X.astype('float64')

X_opt = X[:,[0,1,2,3,4,5]]

regressor_ols = sm.OLS(endog=y,exog=X_opt).fit()

或者

import statsmodels.regression.linear_model as lm

X = np.append(arr = np.ones((50,1)).astype(int),values=X,axis=1)

X.astype('float64')

X_opt = X[:,[0,1,2,3,4,5]]

regressor_ols = lm.OLS(endog=y,exog=X_opt).fit()


regressor_ols = lm.OLS(endog=y,exog=X_opt).fit()
Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\regression\linear_model.py", line 858, in __init__
    super(OLS, self).__init__(endog, exog, missing=missing,
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\regression\linear_model.py", line 701, in __init__
    super(WLS, self).__init__(endog, exog, missing=missing,
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\regression\linear_model.py", line 190, in __init__
    super(RegressionModel, self).__init__(endog, exog, **kwargs)
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\model.py", line 236, in __init__
    super(LikelihoodModel, self).__init__(endog, exog, **kwargs)
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\model.py", line 76, in __init__
    self.data = self._handle_data(endog, exog, missing, hasconst,
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\model.py", line 100, in _handle_data
    data = handle_data(endog, exog, missing, hasconst, **kwargs)
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\data.py", line 671, in handle_data
    return klass(endog, exog=exog, missing=missing, hasconst=hasconst,
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\data.py", line 87, in __init__
    self._handle_constant(hasconst)
  File "C:\Users\hp\PycharmProjects\DataScientist\venv\lib\site-packages\statsmodels\base\data.py", line 132, in _handle_constant
    if not np.isfinite(exog_max).all():
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Answer 1

這個：

X = np.append(arr = np.ones((50,1)).astype(int),values=X,axis=1)

創建一個 dtype int數組，但您的分類器需要浮點值。 看起來你想用這個來糾正這個問題：

X.astype('float64')

但這沒有任何作用，因為您從未分配給它（正確的是X = X.astype('float64') ）。

我建議您從數組創建中刪除astype(int) ：

X = np.append(arr=np.ones((50,1)), values=X, axis=1)