P
Prateek Coder
Guest
Prateek Coder Asks: How to perform feature engineering on columns with multiple categories?
I want to perform feature engineering on a data that mostly contains textual data and lot of columns with multiple categories like Supervisor, location code, employee class, business unit, job title, etc. What should be the best approach to do this? I have binary encoded the column with 2-3 categories or performed one hot encoding, but these columns contains different categories from 8 to 150. Different location will play major role in prediction, so will the employee class or business unit etc and I believe they will be very important for my model.
I want to perform feature engineering on a data that mostly contains textual data and lot of columns with multiple categories like Supervisor, location code, employee class, business unit, job title, etc. What should be the best approach to do this? I have binary encoded the column with 2-3 categories or performed one hot encoding, but these columns contains different categories from 8 to 150. Different location will play major role in prediction, so will the employee class or business unit etc and I believe they will be very important for my model.
SolveForum.com may not be responsible for the answers or solutions given to any question asked by the users. All Answers or responses are user generated answers and we do not have proof of its validity or correctness. Please vote for the answer that helped you in order to help others find out which is the most helpful answer. Questions labeled as solved may be solved or may not be solved depending on the type of question and the date posted for some posts may be scheduled to be deleted periodically. Do not hesitate to share your thoughts here to help others.