v2.3.0

• add Tree-structured optimization algorithm (idea from Hyperopt)
• add Decision-tree optimization algorithm (idea from sklearn)
• enable new optimization parameters for bayes-opt:
  • max_sample_size: maximum number of samples for the gaussian-process-reg to train on. Sampling done by random choice.
  • skip_retrain: skips the retraining of the gaussian-process-reg sometimes during the optimization run. Basically returns multiple predictions for next output (which should be apart from another)