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

Akaike Information Criterion

MuehliManMuehliMan Member Posts: 85 Maven
edited November 2018 in Help
Hi all,

if it possible to calculate the Akaike Information Criterion or even better the Schwarz Infoprmation Criterion by some Performance Operators?
I would like to use it for the Optimize Selection subprocess.

Best,
Markus

Answers

  • landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
    Hi,
    the AIC isn't available in RapidMiner and that has a reason: AIC is only a heuristic to estimate a test error based upon the training error. It is much more valid to estimate this test error by applying a cross-validation.
    If you want to add such an criterion, how would you calculate the number of parameters a model like the SVM or KNN has? I don't know if this is always determined.

    Greetings,
      Sebastian
Sign In or Register to comment.