Opened 12 years ago
Last modified 5 years ago
#1973 closed enhancement
Linear regression models with more than 256 variables are not supported — at Version 1
| Reported by: | swinkler | Owned by: | mkommend |
|---|---|---|---|
| Priority: | medium | Milestone: | HeuristicLab 3.3.16 |
| Component: | Algorithms.DataAnalysis | Version: | trunk |
| Keywords: | Cc: | sschalle |
Description (last modified by gkronber)
Linear regression crashes if more than 256 input features are to be used. (The number of subtrees of the tree representing the linear model is too big.)
Change History (1)
comment:1 Changed 12 years ago by gkronber
- Description modified (diff)
- Summary changed from Problem with linear regression if number of variables > 256 to Linear regression models with more than 256 variables are not supported
Note: See
TracTickets for help on using
tickets.
I'm tempted to reject this ticket, as it is unlikely that this would produce an useful solution. If we allow more than 256 variables I'd prefer that we produce a different kind of model (no symbolic expression tree) in such cases.
For me the actual issue is that we do not have standard feature selection methods for LR or regularized linear models.
More discussion is needed before we decide on the further steps.