Opened 2 years ago

Closed 21 months ago

#2449 closed defect (done)

Persistence of Gaussian process models is inefficient

Reported by: gkronber Owned by: gkronber
Priority: medium Milestone: HeuristicLab 3.3.13
Component: Algorithms.DataAnalysis Version: 3.3.12
Keywords: Cc:

Description

It is not necessary to persist the full covariance matrix for the model as it could be recalculated from the training data. Similarly to the random forest model it is only necessary to store all parameters of the model and the original training data set.

Change History (5)

comment:1 Changed 2 years ago by gkronber

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

comment:2 Changed 2 years ago by gkronber

r12819: improved persistence of GaussianProcessModel (Cholesky decomposed covariance matrix is not stored and recalculated lazily)

comment:3 Changed 2 years ago by gkronber

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

comment:4 Changed 22 months ago by mkommend

  • Owner changed from mkommend to gkronber
  • Status changed from reviewing to readytorelease

Reviewed r12819.

comment:5 Changed 21 months ago by gkronber

  • Resolution set to done
  • Status changed from readytorelease to closed

r13052: merged r12819 from trunk to stable

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