From: Jérôme Benoit Date: Mon, 14 Apr 2025 10:29:45 +0000 (+0200) Subject: perf(qav3): fine tune prediction thresholds temperature X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=abad729bc6b632e951610e31cbba5647ca4a342f;p=freqai-strategies.git perf(qav3): fine tune prediction thresholds temperature Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 62cec4c..2bdf26c 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -44,7 +44,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): https://github.com/sponsors/robcaulk """ - version = "3.7.9" + version = "3.7.10" @cached_property def _optuna_config(self) -> dict: @@ -372,7 +372,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel): def min_max_pred(self, pred_df: pd.DataFrame) -> tuple[float, float]: temperature = float( - self.freqai_info.get("prediction_thresholds_temperature", 120.0) + self.freqai_info.get("prediction_thresholds_temperature", 150.0) ) min_pred = smoothed_min( pred_df[EXTREMA_COLUMN],