The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
Regression issue
Learner I
Hi everybody
I am using linear regression operatore. everything is fine except this issue. I have 15 attributes for linear regression. I use feature selection M5 prime but the final model is weird. I receive "?" instead of numbers in the p-value column. when I remove one attribute form the data, the final result doesn't have "?". Also, when I replace M5 prime with greedy feature selection, the model is different but it doesn't face that problem.
Is there any limitation in linear regression and the number of attributes?
Thank you so much for your favorable responses.
I am using linear regression operatore. everything is fine except this issue. I have 15 attributes for linear regression. I use feature selection M5 prime but the final model is weird. I receive "?" instead of numbers in the p-value column. when I remove one attribute form the data, the final result doesn't have "?". Also, when I replace M5 prime with greedy feature selection, the model is different but it doesn't face that problem.
Is there any limitation in linear regression and the number of attributes?
Thank you so much for your favorable responses.
0
Answers
Did you check the parameters regarding removing collinear features? What about adding bias? Both of those can contribute to issues with calculating the p-values.
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts