Opened 13 months ago

Last modified 3 months ago

#2898 assigned enhancement

Generalized additive models (GAM)

Reported by: gkronber Owned by: gkronber
Priority: medium Milestone: HeuristicLab 3.3.x Backlog
Component: Algorithms.DataAnalysis Version: branch
Keywords: Cc:

Description

Generalized additive models would be a great addition to the set of data-based modeling algorithms.

Feature wishlist:

  • Base-learner for the terms is configurable (default: smoothing spline or penalized regression spline). E.g. it would be great if we could use an efficient symbolic regression solver as base learner.
  • Individually adjustable smoothing or regularization parameter for each term.
  • Automatic selection of smoothing or regularization parameter for each term ideally based on generalized cross-validation (GCV).
  • The variables allowed in each term are configureable.

Idea for a first prototype:

  • Only uni-variate terms are allowed
  • Use alglib penalized regression spline for each term
  • The variables together with penalization parameters for each term are read from a list (algorithm parameter)

Change History (5)

comment:1 Changed 13 months ago by gkronber

  • Owner set to gkronber
  • Status changed from new to accepted

comment:2 Changed 13 months ago by gkronber

r15774: created branch

comment:3 Changed 13 months ago by gkronber

  • Owner changed from gkronber to lkammere
  • Status changed from accepted to reviewing

r15775: added simple implementation of GAM based on uni-variate penalized regression splines with the same penalization factor for each term

comment:4 Changed 3 months ago by gkronber

  • Milestone changed from HeuristicLab 4.x Backlog to HeuristicLab 3.3.16
  • Owner changed from lkammere to gkronber
  • Status changed from reviewing to assigned

comment:5 Changed 3 months ago by gkronber

  • Milestone changed from HeuristicLab 3.3.16 to HeuristicLab 3.3.x Backlog
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