Skip to content

Instantly share code, notes, and snippets.

@shaan-shah

shaan-shah/rf-explanation5.py

Created August 18, 2020 14:04
Show Gist options
  • Save shaan-shah/1543383e4b761adc3d8fd5b4f3985116 to your computer and use it in GitHub Desktop.
Save shaan-shah/1543383e4b761adc3d8fd5b4f3985116 to your computer and use it in GitHub Desktop.
Download ZIP
This made to demonstrate code on medium.
Raw
rf-explanation5.py
def auto_predictor(Target_Variable,data_raw,n_valid,data_to_predict,date_column=None):
if date_column:
data_raw['{}'.format(date_column)]= pd.to_datetime(data_raw['{}'.format(date_column)])
data_to_predict['{}'.format(date_column)]= pd.to_datetime(data_to_predict['{}'.format(date_column)])
intermed=data_trainer(Target_Variable=Target_Variable,data_raw=data_raw,n_valid=n_valid,date_column=date_column)
return(auto_applyer(leaf_value=intermed[0],feature_value=intermed[1],feature_list=intermed[2],df_raw1=data_raw,df_test=data_to_predict,target_column=Target_Variable,date_column=date_column))
else:
intermed=data_trainer(Target_Variable=Target_Variable,data_raw=data_raw,n_valid=n_valid)
return(auto_applyer(leaf_value=intermed[0],feature_value=intermed[1],feature_list=intermed[2],df_raw1=data_raw,df_test=data_to_predict,target_column=Target_Variable))
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment