- Mar 04, 2020
-
-
Léo Bouscarrat authored
-
Léo Bouscarrat authored
-
Léo Bouscarrat authored
-
Léo Bouscarrat authored
Merge branch '17-adding-new-datasets' of https://gitlab.lis-lab.fr/luc.giffon/bolsonaro into 17-adding-new-datasets
-
Léo Bouscarrat authored
-
- Feb 28, 2020
-
-
Charly Lamothe authored
-
Léo Bouscarrat authored
-
Charly Lamothe authored
Resolve "Experiment pipeline" Closes #12 See merge request !9
-
- Feb 26, 2020
-
-
Charly Lamothe authored
Resolve "Correction of multiclass classif" See merge request !11
-
Léo Bouscarrat authored
-
- Feb 04, 2020
-
-
Charly Lamothe authored
Add Paolo's first implementation of this paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2822360/
-
- Jan 09, 2020
-
-
Charly Lamothe authored
- Add new results for stage4.
-
- Jan 08, 2020
-
-
Charly Lamothe authored
-
Charly Lamothe authored
-
Charly Lamothe authored
- Add stage4 (results and experiments); - Do not save model object.
-
- Jan 07, 2020
-
-
Charly Lamothe authored
- Add diamonds in experiment scripts and add factorize run_compute_results.sh script; - Add best params for diamonds dataset.
-
- Jan 06, 2020
-
-
Charly Lamothe authored
-
Charly Lamothe authored
Add quick working version of diamonds dataset to test that the improvement of OMP are consistent in other regression tasks.
-
Charly Lamothe authored
-
- Dec 29, 2019
-
-
Charly Lamothe authored
- Remove extracted_forest_sizes_number parameter from compute_results.py and retreive the value instead; - Add almost all remaining experiment config files of stages 1, 2 and 3; - Add almost all remaining result plots of stages 1, 2 and 3; - Add some temporary scripts to run all stages experiments.
-
- Dec 26, 2019
-
-
Charly Lamothe authored
- Add command lines example for stage 3; - Add experiment_id option that is useful sometimes; - Fix subsets_used param; - Remove experiment_id in config experiment file names; - Add config experiment files for stages 2 and 3; - Add results for stages 2 and 3 (california_housing).
-
Charly Lamothe authored
- Fix possible issues for extracted forest sizes computation: around to reduce possible zeroes and remove duplicates; - Create output experiment stage dir if not exists; - Add base_score_metric to model raw results class; - Add best params for lfw_pairs (maybe try with a larger number of random seeds since the score is not that high).
-
- Dec 25, 2019
-
-
Charly Lamothe authored
- Remove useless getter in Dataset class.
-
- Dec 20, 2019
-
-
Charly Lamothe authored
-
Charly Lamothe authored
-
Charly Lamothe authored
- Even if hyperparameters file is ignore with skip_best_hyperparams option, still use the same forest_size to be comparable; - Update experiment files for stage1 wo_param experiments (using the same forest size as the with_params experiments); - In compute_results: remove useless folder creation; temporary add extracted_forest_sizes_number option to specify the extracted forest sizes number; temporary not plotting train and dev losses in stage1 loss values figure; - In plotter, clean-up stage1 figure generation; - Add first unbiased losses plot (stage1: best params vs default params in california housing dataset).
-
Charly Lamothe authored
-
Charly Lamothe authored
-
Charly Lamothe authored
-
- Dec 19, 2019
-
-
Léo Bouscarrat authored
-
Léo Bouscarrat authored
-
Charly Lamothe authored
-
Charly Lamothe authored
-
Charly Lamothe authored
- Fix some variable names; - Add exp files of stage1 for california housing
-
Charly Lamothe authored
- Reduce the extracted forest sizes upper bound and number because OMP seems to converge only with small forest sizes; - Add extraction_strategy parameter in order to save base forest and the forests trained with the same size as the extracted forest sizes used in the experiment that used OMP.
-
- Dec 18, 2019
-
-
Charly Lamothe authored
POC of possible wrong way to compute best hyperparams. Are there the best only before the application of OMP extraction?
-
Charly Lamothe authored
- Definitely use the correct forest size (either the one from best hyperparameters or the one specified in parameter); - Use a number of extracted forest sizes proportional as the forest size instead of fixed forest size; - Add an option to save the current command line name instead of using the unamed directory; - Add new california housing dataset best hyperparameters, and convert all value types that are number from string to int/float in other best hyperparameter files; - Remove useless code from compute_results.py in prevision of the changes; - Before best hyperparameters saving, save number as int or float instead of string; - Add job_number option for parallelisation in both train.py and compute_hyperparameters.py scripts; - Clean-up TODO list.
-
Charly Lamothe authored
- Add new best params for 7 datasets.
-
- Dec 01, 2019
-
-
Charly Lamothe authored
-
Charly Lamothe authored
-