BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
rkarr5
Calcite | Level 5

Hi,

 

Can anyone help me with this. I am doing data mining on the Chicago towing data which has tow data, make, towed to address, tow facility phone. I am trying to do a research on how many vehicles are towed to a particular address in the weekends and week days. For that, I choose tow to address as my target variable. Can anyone help me regarding the dummy variables for this variable. 

 

Regards,

Ravi Teja Karri.

1 ACCEPTED SOLUTION

Accepted Solutions
Reeza
Super User

There are no dummy variables and created to the data set if that is what you're expecting.

 

The process will treat the variable according to whatever model you implemented. If you're not sure and really want to see if it does it correctly you can do one manually and one automatically and see if you get the same output. Make sure the correct parameterization method is selected in both if you're looking at a logistic regression for example. 

 

Or look at the scoring code, there should be something in there, especially if you look at the data step. 

View solution in original post

4 REPLIES 4
Reeza
Super User

SAS typically creates the dummy variables needed, you need to make sure it's set to the correct variable type i.e. nominal and target.

rkarr5
Calcite | Level 5

Hi Reeza,

 

Thanks for the reply. We set the role of target variable to target and Level to nominal as it having string of characters and numbers. But there is no dummy variable created in our project. Can you help us in  determining whether the dummy variables created or not? 

 

Regards,

Ravi Teja Karri.

 

 

Reeza
Super User

There are no dummy variables and created to the data set if that is what you're expecting.

 

The process will treat the variable according to whatever model you implemented. If you're not sure and really want to see if it does it correctly you can do one manually and one automatically and see if you get the same output. Make sure the correct parameterization method is selected in both if you're looking at a logistic regression for example. 

 

Or look at the scoring code, there should be something in there, especially if you look at the data step. 

rkarr5
Calcite | Level 5

Thanks for that. It helped me a lot.

SAS Innovate 2025: Save the Date

 SAS Innovate 2025 is scheduled for May 6-9 in Orlando, FL. Sign up to be first to learn about the agenda and registration!

Save the date!

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 4 replies
  • 1315 views
  • 0 likes
  • 2 in conversation