- 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).

- Fix some variable names;
- Add exp files of stage1 for california housing

- 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.