BookmarkSubscribeRSS Feed
Bipin_gaud
Calcite | Level 5

friends, suppose i have 200 variables and i have to make a linear regression model on that , then what is the best  way of understanding each variable. or i should first reduce the variables by using factor analysis or using automatic linear regression to finalise the significance variables?

1 REPLY 1
jo_rod
Obsidian | Level 7

That depends on what question you are trying to answer. I'm assuming that not all of the variables are actual covariates that "need" to be in the model. Going through each of the 200 variables is pretty much a "digging" process, and eventually the likelihood is that you'll end up with one that is significant, even if it doesn't make sense to have it in the regression model.

sas-innovate-2024.png

Available on demand!

Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.

 

Register now!

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
  • 1 reply
  • 778 views
  • 2 likes
  • 2 in conversation