1. 10 Mar, 2020 1 commit
  2. 06 Mar, 2020 3 commits
  3. 28 Feb, 2020 3 commits
  4. 26 Feb, 2020 1 commit
  5. 09 Jan, 2020 1 commit
  6. 08 Jan, 2020 2 commits
  7. 29 Dec, 2019 1 commit
  8. 26 Dec, 2019 1 commit
    • Charly Lamothe's avatar
      - Add code for stages 2 and 3 results; · 8de5e96a
      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).
      8de5e96a
  9. 20 Dec, 2019 3 commits
  10. 19 Dec, 2019 4 commits
  11. 18 Dec, 2019 2 commits
    • Charly Lamothe's avatar
      POC of possible wrong way to compute best hyperparams. Are there the best only... · fd6dbc7b
      Charly Lamothe authored
      POC of possible wrong way to compute best hyperparams. Are there the best only before the application of OMP extraction?
      fd6dbc7b
    • Charly Lamothe's avatar
      - Add an option to not use the best hyperparameters file; · 880ff78f
      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.
      880ff78f
  12. 09 Nov, 2019 2 commits
  13. 06 Nov, 2019 2 commits
  14. 05 Nov, 2019 3 commits
  15. 04 Nov, 2019 2 commits
    • Charly LAMOTHE's avatar
      - In compute_results, add loadenv, load raw results, and update experiment_ids... · 8b8eb9a5
      Charly LAMOTHE authored
      - In compute_results, add loadenv, load raw results, and update experiment_ids so that it's possible to specify a list of experiments ids. The default behavior is to load all exp ids;
      - Fix normalization option in train.py. By default it normalizes D, and it doesn't when specify wo_normalization option;
      - Fix logger.warn to logger.warning in train.py
      - Replace the dumping of result in trainer.py by a dedicated class to save and load the trained model and training metadatas: model_raw_results.py;
      - Rename too long func DatasetLoader.load_from_name to DatasetLoader.load;
      - Add loading functions in dataset_parameters and model_parameters;
      - Set console logging level to INFO to summarize the most important console logs;
      - Add a load function in model_factory;
      - In omp_forest_regressor, move private funcs to the bottom of the file.
      
      TODO: compute the plot from the loaded raw results in compute_results file.
      8b8eb9a5
    • Luc Giffon's avatar
      rassemble le code dans un répertoire 'code' + update setup.py en conséquence +... · 87115964
      Luc Giffon authored
      rassemble le code dans un répertoire 'code' + update setup.py en conséquence + ajoute scikit-learn à requirements.txt
      87115964
  16. 03 Nov, 2019 1 commit