From: Jérôme Benoit Date: Fri, 25 Apr 2025 09:19:27 +0000 (+0200) Subject: perf(qav3): fine tune entry signal thresholds X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;ds=inline;p=freqai-strategies.git perf(qav3): fine tune entry signal thresholds Signed-off-by: Jérôme Benoit --- diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 18f1751..d1b1a44 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -382,11 +382,11 @@ class QuickAdapterRegressorV3(BaseRegressionModel): label_period_candles: int, ) -> tuple[float, float]: temperature = float( - self.freqai_info.get("prediction_thresholds_temperature", 125.0) + self.freqai_info.get("prediction_thresholds_temperature", 175.0) ) extrema = pred_df[EXTREMA_COLUMN].iloc[ -( - max(2, int((fit_live_predictions_candles / 2) / label_period_candles)) + max(2, int(fit_live_predictions_candles / label_period_candles)) * label_period_candles ) : ] @@ -972,7 +972,7 @@ def label_objective( df = df.iloc[ -( - int(fit_live_predictions_candles / label_period_candles) + max(2, int(fit_live_predictions_candles / label_period_candles)) * label_period_candles ) : ]