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

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* 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
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run_pipeline.py
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@@ -40,6 +40,7 @@ def pipeline(project_name:str, wandb, sweep:bool, model_config:dict, training_co
target_returns = target_returns,
models = model_config['level_1_models'],
method = data_config['method'],
expanding_window = training_config['expanding_window'],
sliding_window_size = training_config['sliding_window_size'],
retrain_every = training_config['retrain_every'],
scaler = training_config['scaler'],
@@ -64,6 +65,7 @@ def pipeline(project_name:str, wandb, sweep:bool, model_config:dict, training_co
target_returns = target_returns,
models = model_config['level_2_models'],
method = data_config['method'],
expanding_window = training_config['expanding_window'],
sliding_window_size = training_config['sliding_window_size'],
retrain_every = training_config['retrain_every'],
scaler = training_config['scaler'],