我已經(jīng)開(kāi)始學(xué)習(xí)機(jī)器學(xué)習(xí)，并且正在嘗試實(shí)現(xiàn)線性回歸反向消除。這是代碼：import statsmodels.api as smx = sm.add_constant(x)x_opt = x[:,[0,1,2,3,4,5]]regressor_OLS = sm.OLS(endog=y,exog=x_opt)這是錯(cuò)誤：Traceback (most recent call last): File "<input>", line 1, in <module> File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\regression\linear_model.py", line 859, in __init__ hasconst=hasconst, **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\regression\linear_model.py", line 702, in __init__ weights=weights, hasconst=hasconst, **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\regression\linear_model.py", line 190, in __init__ super(RegressionModel, self).__init__(endog, exog, **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\base\model.py", line 236, in __init__ super(LikelihoodModel, self).__init__(endog, exog, **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\base\model.py", line 77, in __init__ **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\base\model.py", line 100, in _handle_data data = handle_data(endog, exog, missing, hasconst, **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\base\data.py", line 672, in handle_data **kwargs) File "C:\Users\ewasy\AppData\Local\Programs\Python\Python37\lib\site-packages\statsmodels\base\data.py", line 87, in __init__ self._handle_constant(hasconst)這是變量 x 的 2 行：array([[1.0, 0.0, 1.0, 2.016411493158463, 0.560752914530775,2.153943088571744], [1.0, 0.0, 0.0, 1.9558603364325031, 1.0828065830760816,1.9236003956421444]], dtype=object)這是變量 y 的 2 行：array([[2.01120333],[1.99942997]])
2 回答
慕工程0101907
TA貢獻(xiàn)1887條經(jīng)驗(yàn) 獲得超5個(gè)贊
問(wèn)題是在您的代碼x中有dtype=object而不是dtype=float, 即x不是數(shù)字變量，因此它不能用作回歸量。一旦x轉(zhuǎn)換為float您的代碼就可以工作。
心有法竹
TA貢獻(xiàn)1866條經(jīng)驗(yàn) 獲得超5個(gè)贊
import statsmodels.api as sm
def model(X,y):
X=sm.add_constant(X)
lm_model=sm.OLS(y,X).fit()
print(lm_model.summary())
return X
X_train1=model(X_train_rfe,y_train)
如果您想查看基本的詳細(xì) ML 問(wèn)題：https ://github.com/ds-souvik/Machine-Learning-Basic-Intermediate-Expert./tree/master/10%20Linear%20Regression-%20BoomBikes%20Bike%20Sharing %20服務(wù)%20業(yè)務(wù)%20案例
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