Optuna support for XGBoost, MLP and CatBoost ALpha360 dataset

[igor17400]

Description

Optuna is an open source hyperparameter optimization framework to automate hyperparameter search.

Motivation and Context

All models should have optuna hyperparameter search implemented

How Has This Been Tested?

• [x] Pass the test by running: pytest qlib/tests/test_all_pipeline.py under upper directory of qlib.
• [x] If you are adding a new feature, test on your own test scripts.

Just follow the readme.md file inside example/hyperparameter in order to test it.

Screenshots of Test Results (if appropriate):

1. optuna create-study --study <<Model>>_360 --storage sqlite:///db.sqlite3 for example we can change <<Model>> for CatBoost and run optuna create-study --study CatBoost_360 --storage sqlite:///db.sqlite3
2. optuna-dashboard --port 5000 --host 0.0.0.0 sqlite:///db.sqlite3
3. Open the dashboard and you should see images as the ones below

Types of changes

• [ ] Fix bugs
• [x] Add new feature
• [ ] Update documentation