diff --git a/autopeptideml/data/h_param_search/gradboost_class.yml b/autopeptideml/data/h_param_search/gradboost_class.yml index 3f4b6b5..0aa22e9 100644 --- a/autopeptideml/data/h_param_search/gradboost_class.yml +++ b/autopeptideml/data/h_param_search/gradboost_class.yml @@ -1,7 +1,7 @@ n_estimators: type: int - min: 10 - max: 1000 + min: 8 + max: 256 log: True learning_rate: diff --git a/autopeptideml/data/h_param_search/gradboost_reg.yml b/autopeptideml/data/h_param_search/gradboost_reg.yml index cc9d978..ae59404 100644 --- a/autopeptideml/data/h_param_search/gradboost_reg.yml +++ b/autopeptideml/data/h_param_search/gradboost_reg.yml @@ -1,7 +1,7 @@ n_estimators: type: int - min: 10 - max: 1000 + min: 8 + max: 256 log: True learning_rate: diff --git a/autopeptideml/data/h_param_search/lightgbm_class.yml b/autopeptideml/data/h_param_search/lightgbm_class.yml index 140f2f3..bcd0405 100644 --- a/autopeptideml/data/h_param_search/lightgbm_class.yml +++ b/autopeptideml/data/h_param_search/lightgbm_class.yml @@ -1,7 +1,7 @@ n_estimators: type: int - min: 10 - max: 500 + min: 8 + max: 256 log: False class_weight: @@ -11,13 +11,13 @@ class_weight: num_leaves: type: int min: 8 - max: 1024 + max: 256 log: False max_depth: type: int min: 2 - max: 10 + max: 8 log: False subsample: diff --git a/autopeptideml/data/h_param_search/lightgbm_reg.yml b/autopeptideml/data/h_param_search/lightgbm_reg.yml index 4cf9a97..1ce1f55 100644 --- a/autopeptideml/data/h_param_search/lightgbm_reg.yml +++ b/autopeptideml/data/h_param_search/lightgbm_reg.yml @@ -1,19 +1,19 @@ n_estimators: type: int - min: 10 - max: 500 + min: 8 + max: 256 log: False num_leaves: type: int min: 8 - max: 1024 + max: 256 log: False max_depth: type: int min: 2 - max: 10 + max: 8 log: False subsample: diff --git a/autopeptideml/data/h_param_search/rf_class.yml b/autopeptideml/data/h_param_search/rf_class.yml index 94a9ae8..7cc7179 100644 --- a/autopeptideml/data/h_param_search/rf_class.yml +++ b/autopeptideml/data/h_param_search/rf_class.yml @@ -1,7 +1,7 @@ n_estimators: type: int min: 10 - max: 1000 + max: 100 log: True max_depth: diff --git a/autopeptideml/data/h_param_search/rf_reg.yml b/autopeptideml/data/h_param_search/rf_reg.yml index b95eb5b..7c17c73 100644 --- a/autopeptideml/data/h_param_search/rf_reg.yml +++ b/autopeptideml/data/h_param_search/rf_reg.yml @@ -1,7 +1,7 @@ n_estimators: type: int min: 10 - max: 1000 + max: 100 log: True max_depth: diff --git a/autopeptideml/data/h_param_search/xgboost_class.yml b/autopeptideml/data/h_param_search/xgboost_class.yml index 062f172..793a6c6 100644 --- a/autopeptideml/data/h_param_search/xgboost_class.yml +++ b/autopeptideml/data/h_param_search/xgboost_class.yml @@ -1,7 +1,7 @@ n_estimators: type: int - min: 10 - max: 1000 + min: 8 + max: 256 log: True learning_rate: @@ -87,7 +87,6 @@ grow_policy: - depthwise - lossguide - sampling_method: type: fixed value: uniform @@ -102,4 +101,4 @@ verbose: n_jobs: type: fixed - value: 1 \ No newline at end of file + value: 1 diff --git a/autopeptideml/data/h_param_search/xgboost_reg.yml b/autopeptideml/data/h_param_search/xgboost_reg.yml index 5a54eab..2f2166a 100644 --- a/autopeptideml/data/h_param_search/xgboost_reg.yml +++ b/autopeptideml/data/h_param_search/xgboost_reg.yml @@ -1,7 +1,7 @@ n_estimators: type: int - min: 10 - max: 1000 + min: 8 + max: 256 log: True learning_rate: diff --git a/autopeptideml/train/architectures.py b/autopeptideml/train/architectures.py index 444b74a..4512dac 100644 --- a/autopeptideml/train/architectures.py +++ b/autopeptideml/train/architectures.py @@ -12,7 +12,7 @@ from skl2onnx import to_onnx -SKLEARN_MODELS = ['knn', 'svm', 'rf', 'gradboost', 'logreg', 'linreg'] +SKLEARN_MODELS = ['knn', 'svm', 'rf', 'gradboost'] ALL_MODELS = SKLEARN_MODELS + ['lightgbm', 'xgboost'] diff --git a/autopeptideml/train/trainer.py b/autopeptideml/train/trainer.py index b3b672a..682fcf5 100644 --- a/autopeptideml/train/trainer.py +++ b/autopeptideml/train/trainer.py @@ -517,9 +517,12 @@ def hpo( "Please try: `pip install optuna`") if verbose < 1: optuna.logging.set_verbosity(optuna.logging.ERROR) - elif verbose < 3: + elif verbose == 1: optuna.logging.set_verbosity(optuna.logging.WARNING) - + elif verbose == 2: + optuna.logging.set_verbosity(optuna.logging.INFO) + elif verbose == 3: + optuna.logging.set_verbosity(optuna.logging.DEBUG) if isinstance(x, np.ndarray): x = {'default': x} @@ -567,7 +570,7 @@ def hpo( ) self.study.optimize(self._hpo_step, n_trials=self.n_trials, callbacks=[callback], - gc_after_trial=True, show_progress_bar=verbose == 2) + gc_after_trial=True, show_progress_bar=verbose >= 2) @classmethod def load_from_db(