I have developed a Linear Regression model using SKlearn that involves dummy variables (due to categorical variables as input). I created a pickle file and loaded it in another session.
from sklearn.externals import joblib
loaded_model = joblib.load(‘LR_Model.pkl’)
When performing Out-Of-Sample validation on new data set (much smaller than trained), I again transform the categorical variables into dummy variables.
for column in validation_df.columns:
When I try to predict on new data set (Y_predicted = loaded_model.predict(validation_df)),
I get the below error (full error in image):
ValueError: shapes (1349,1000) and (2017,2) not aligned: 1000 (dim 1) != 2017 (dim 0)