From: Jérôme Benoit Date: Sat, 30 Aug 2025 22:14:52 +0000 (+0200) Subject: perf(qav3): skip training sets sizing when necessary X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=8803d9c54579490d1f93340559211dd1b5124ce7;p=freqai-strategies.git perf(qav3): skip training sets sizing when necessary Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index b6da415..89e9448 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -340,9 +340,13 @@ class QuickAdapterRegressorV3(BaseRegressionModel): direction=optuna.study.StudyDirection.MINIMIZE, ) + optuna_hp_value = self.get_optuna_value(dk.pair, "hp") optuna_train_params = self.get_optuna_params(dk.pair, "train") - if optuna_train_params and self.optuna_params_valid( - dk.pair, "train", train_study + optuna_train_value = self.get_optuna_value(dk.pair, "train") + if ( + optuna_train_params + and self.optuna_params_valid(dk.pair, "train", train_study) + and optuna_train_value < optuna_hp_value ): train_period_candles = optuna_train_params.get("train_period_candles") if isinstance(train_period_candles, int) and train_period_candles > 0: @@ -355,6 +359,10 @@ class QuickAdapterRegressorV3(BaseRegressionModel): X_test = X_test.iloc[-test_period_candles:] y_test = y_test.iloc[-test_period_candles:] test_weights = test_weights[-test_period_candles:] + elif optuna_train_value >= optuna_hp_value: + logger.warning( + f"{dk.pair}: Optuna train RMSE {format_number(optuna_train_value)} is not better than HPO RMSE {format_number(optuna_hp_value)}, skipping training sets sizing optimization" + ) eval_set, eval_weights = QuickAdapterRegressorV3.eval_set_and_weights( X_test,