From: Jérôme Benoit Date: Mon, 27 Jan 2025 11:06:44 +0000 (+0100) Subject: perf: refine the candles window step search X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=cca81ddd2ff789a98acaf32634f3573d3173824a;p=freqai-strategies.git perf: refine the candles window step search The search space is increased, optuna will takes longer. Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/config-template.json b/quickadapter/user_data/config-template.json index e4da3ce..4c3db3e 100644 --- a/quickadapter/user_data/config-template.json +++ b/quickadapter/user_data/config-template.json @@ -119,7 +119,7 @@ "conv_width": 1, "purge_old_models": 2, "expiration_hours": 12, - "train_period_days": 14, + "train_period_days": 30, "live_retrain_hours": 0.5, "backtest_period_days": 2, "write_metrics_to_disk": false, diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py index 91cf269..bbaccb3 100644 --- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py +++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py @@ -223,7 +223,7 @@ def objective(trial, X, y, weights, X_test, y_test, params): "reg_lambda": trial.suggest_loguniform("reg_lambda", 1e-8, 10.0), } params = {**params, **study_params} - window = trial.suggest_int("train_period_candles", 1152, 17280, step=300) + window = trial.suggest_int("train_period_candles", 1152, 17280, step=100) # Fit the model model = LGBMRegressor(**params) diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py index 082c0bd..6c053d6 100644 --- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py +++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py @@ -231,7 +231,7 @@ def objective(trial, X, y, weights, X_test, y_test, params): ], } params = {**params, **study_params} - window = trial.suggest_int("train_period_candles", 1152, 17280, step=300) + window = trial.suggest_int("train_period_candles", 1152, 17280, step=100) # Fit the model model = XGBRegressor(**params)