I am using PyCaret and get an error.
AttributeError: 'SimpleImputer' object has no attribute '_validate_data'
Trying to create a basic instance.
# 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)
All my variables are numeric (I coerced two of them, which are boolean). My target variable is label and this is by default.
I also installed PyCaret, imported its regression, and re-installed scikit learn, imported SimpleImputer as 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
My traceback is the following:

The problem here is with the imputation. The default per pycaret documentation is 'simple' but in this case, you need to make that imputation_type='iterative' for it to work.
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