Closed jakob-wirbel closed 4 years ago
Does not seem needed for lasso_ll
(or rather classif.LiblineaRL1LogReg
) models, since the call is not stored in the learner.model
wrapped object.
Actually, here are example object.size
results for the list of models using the data in the vignette:
# A tibble: 3 x 2
ml.method size
<chr> <chr>
1 lasso 4.1 Mb
2 lasso_ll 0.8 Mb
3 randomForest 11.3 Mb
Unfortunately, i did not see a way to reduce the size of the random forest models :-(
But, the size of the lasso models could be decreased from 4.1 Mb to 2 Mb
For glmnet models, 90% of the model size comes from the stored
call
in thelearner.model$glmnet.fit
part of the wrapped model. I don't think the call is needed and we could just delete it within the siamcat function already in order to have smaller models, which do not take too much space when exported as RData object