logger_factory.py

- 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.