Dear Consultants,
I have dataset (599*14747) as follows: 599 observation for 6 classes and 14746 independent varaiables (predictors). the predictors are interval and the target(response) variable is nominal(categorical). I tried to find correlation to reduce the irrelevant variables using Pearson correlation but I think it finds only linear relationship only, also Pearson are changed with outliers. I need to know the optimal way to find the variables importance using statistical and data mining methods to improve the classification. notes: I have SAS Enterprise Miner 13.2
Hi Hussein,
I remember we were discussing techniques for variable selection and dimension reduction in an earlier thread ().
Do some of those techniques give you a better model than others?
Different techniques have different pros and cons. Many times you have to try a lot of them to see which one is most helpful to your data and business problem.
The course Advanced Predictive Modeling Using SAS Enterprise Miner is a good hands-on refresher of all the tools you have in your toolkit. I am considering taking that class again :smileysilly:
Post some of your findings if you have a chance.
Thanks!
-Miguel
Hi Hussein,
I remember we were discussing techniques for variable selection and dimension reduction in an earlier thread ().
Do some of those techniques give you a better model than others?
Different techniques have different pros and cons. Many times you have to try a lot of them to see which one is most helpful to your data and business problem.
The course Advanced Predictive Modeling Using SAS Enterprise Miner is a good hands-on refresher of all the tools you have in your toolkit. I am considering taking that class again :smileysilly:
Post some of your findings if you have a chance.
Thanks!
-Miguel
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 16. Read more here about why you should contribute and what is in it for you!
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.