how to assign back categorical variables to train and test data after training and testing using inverse_transform? how to assign back categorical variables to train and test data after training and testing using inverse_transform? Like training and testing, data will have encoded numerical values. So, how to assign back categorical values to those variables to train and test dataset after training and testing?
Please help me with this.
If you are using ordinal data
Use this to encode
  
from sklearn.preprocessing import OrdinalEncoder
oe=OrdinalEncoder()
social['Gender']=oe.fit_transform(social[['Gender']])

Use this to decode
social['Gender']=oe.inverse_transform(social[['Gender']])



If you are using nominal variables
Use this to encode
from sklearn.preprocessing import OneHotEncoder
  
ohe = OneHotEncoder()

temp_var= ohe.fit_transform(social[['Gender']]) 

Use this to decode
temp_var2=ohe.inverse_transform(temp_var)


Hope it helps