我正在使用PyCaret,但出现了一个错误
AttributeError: 'SimpleImputer' object has no attribute '_validate_data'
正在尝试创建基本实例
# Create a basic PyCaret instance
import pycaret
from pycaret.regression import *
mlb_pycaret = setup(data = pycaret_df, target = 'pts', train_size = 0.8, numeric_features = ['home',
'first_time_pitcher'], session_id = 123)
我所有的变量都是数值型的(我强制了其中两个,它们是布尔型的)。我的目标变量是label
,这是默认值
我还安装了PyCaret
,导入了它的回归,并重新安装了scikit learn
,将SimpleImputer
导入为from sklearn.impute import SimpleImputer
OBP_avg Numeric
SLG_avg Numeric
SB_avg Numeric
RBI_avg Numeric
R_avg Numeric
home Numeric
first_time_pitcher Numeric
park_ratio_OBP Numeric
park_ratio_SLG Numeric
SO_avg_p Numeric
pts_500_parkadj_p Numeric
pts_500_parkadj Numeric
SLG_avg_parkadj Numeric
OPS_avg_parkadj Numeric
SLG_avg_parkadj_p Numeric
OPS_avg_parkadj_p Numeric
pts_BxP Numeric
SLG_BxP Numeric
OPS_BxP Numeric
whip_SO_BxP Numeric
whip_SO_B Numeric
whip_SO_B_parkadj Numeric
order Numeric
ops x pts_500 order15 Numeric
ops x pts_500 parkadj Numeric
ops23 x pts_500 Numeric
ops x pts_500 orderadj Numeric
whip_p Numeric
whip_SO_p Numeric
whip_SO_parkadj_p Numeric
whip_parkadj_p Numeric
pts Label
我的回溯如下:
这里的问题在于插补。默认的perpycaret documentation是“simple”,但在本例中,您需要使该
imputation_type='iterative'
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