feat(Models): added debug_future_lookahead, sped up LogisticRegression & DecisionTreeClassifier (#74)

* feat(Models): added `debug_future_lookahead`, sped up LogisticRegression & DecisionTreeClassifier

* feat(Training): added ability to train on expanding_window

* feat(Models): tuned some hyperparameters, added expanding_window to sweep config, fixed tests

* feat(Models): tune parameters of ensemble models

* fix(Config): use window size that works with ensembling
This commit is contained in:
Mark Aron Szulyovszky
2021-12-22 16:59:03 +01:00
committed by GitHub
parent 25b64f5a3d
commit 6ae8acf70e
11 changed files with 32 additions and 10 deletions
+3 -2
View File
@@ -5,8 +5,9 @@ from models.model_map import model_names_classification, model_names_regression
def get_default_config() -> tuple[dict, dict, dict]:
training_config = dict(
sliding_window_size = 150,
retrain_every = 20,
expanding_window = True,
sliding_window_size = 200,
retrain_every = 100,
scaler = 'minmax', # 'normalize' 'minmax' 'standardize' 'none'
include_original_data_in_ensemble = True,
)