From 7260a71ecbcd55b6bc4f377f5a750df10ecb7e69 Mon Sep 17 00:00:00 2001 From: longyu Date: Fri, 15 Jul 2022 23:02:09 +0200 Subject: [PATCH 1/2] refactor set_weights_higher_recent --- freqtrade/freqai/data_kitchen.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py index f320bdc2f..74d763e1b 100644 --- a/freqtrade/freqai/data_kitchen.py +++ b/freqtrade/freqai/data_kitchen.py @@ -675,12 +675,10 @@ class FreqaiDataKitchen: Set weights so that recent data is more heavily weighted during training than older data. """ - + wfactor = self.config["freqai"]["feature_parameters"]["weight_factor"] weights = np.zeros(num_weights) - for i in range(1, len(weights)): - weights[len(weights) - i] = np.exp( - -i / (self.config["freqai"]["feature_parameters"]["weight_factor"] * num_weights) - ) + weights[1:] = np.exp( + - np.arange(1, len(weights)) / (wfactor * num_weights))[::-1] return weights def append_predictions(self, predictions, do_predict, len_dataframe): From 2fdea6d43a35a82b282fe058b11b78a28bb68435 Mon Sep 17 00:00:00 2001 From: longyu Date: Sat, 16 Jul 2022 15:02:30 +0200 Subject: [PATCH 2/2] print start and end date of the train/test data --- freqtrade/freqai/prediction_models/BaseRegressionModel.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py index f9a9bb69f..6f345ef67 100644 --- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py +++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py @@ -39,7 +39,10 @@ class BaseRegressionModel(IFreqaiModel): :model: Trained model which can be used to inference (self.predict) """ - logger.info("--------------------Starting training " f"{pair} --------------------") + start_date = unfiltered_dataframe["date"].iloc[0] + end_date = unfiltered_dataframe["date"].iloc[-1] + logger.info("-------------------- Starting training " f"{pair} --------------------") + logger.info("-------------------- Using data " f"from {start_date} to {end_date}--------------------") # filter the features requested by user in the configuration file and elegantly handle NaNs features_filtered, labels_filtered = dk.filter_features(