Mercurial > pylearn
changeset 1201:46527ae6db53
architecture: Clarified what I meant about saving the model
| author | Olivier Delalleau <delallea@iro> |
|---|---|
| date | Mon, 20 Sep 2010 17:05:15 -0400 |
| parents | acfd5e747a75 |
| children | 7fff3d5c7694 |
| files | doc/v2_planning/architecture.txt |
| diffstat | 1 files changed, 12 insertions(+), 0 deletions(-) [+] |
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--- a/doc/v2_planning/architecture.txt Mon Sep 20 11:28:23 2010 -0400 +++ b/doc/v2_planning/architecture.txt Mon Sep 20 17:05:15 2010 -0400 @@ -161,3 +161,15 @@ - Existing objects and code (including dbi and Jobman), with some more pieces to tie things together (Fred B.) +OD comments: We were in a hurry to close the meeting and I did not have time +to really explain what I meant when I suggested we should add the requirement +of saving the final "best" model. What I had in mind is a typical "applied ML" +experiment, i.e. the following approach that hopefully can be understood just +by writing it down in the form of a processing pipeline. The double cross +validation step, whose goal is to obtain an estimate of the generalization +error of our final model, is: + data -> k_fold_outer(preprocessing -> k_fold_inner(dbn -> evaluate) -> select_best -> retrain_on_all_data -> evaluate) -> evaluate +Once this is done, the model we want to save is obtained by doing + data -> preprocessing -> k_fold(dbn -> evaluate) -> select_best -> retrain_on_all_data +and we save + preprocessing -> best_model_selected