From b0ab400ff36b5c60105540ead2c4a6d4ea177b0a Mon Sep 17 00:00:00 2001 From: robcaulk Date: Sat, 17 Jun 2023 15:39:33 +0200 Subject: [PATCH] fix: ensure test_size=0 is still accommodated --- .../freqai/RL/BaseReinforcementLearningModel.py | 11 ++++++----- .../freqai/base_models/BaseClassifierModel.py | 11 ++++++----- .../freqai/base_models/BasePyTorchClassifier.py | 11 ++++++----- .../freqai/base_models/BasePyTorchRegressor.py | 13 ++++++++----- .../freqai/base_models/BaseRegressionModel.py | 16 ++++++++-------- 5 files changed, 34 insertions(+), 28 deletions(-) diff --git a/freqtrade/freqai/RL/BaseReinforcementLearningModel.py b/freqtrade/freqai/RL/BaseReinforcementLearningModel.py index 81cacc055..4f7b55967 100644 --- a/freqtrade/freqai/RL/BaseReinforcementLearningModel.py +++ b/freqtrade/freqai/RL/BaseReinforcementLearningModel.py @@ -126,11 +126,12 @@ class BaseReinforcementLearningModel(IFreqaiModel): dd["train_labels"], dd["train_weights"]) - (dd["test_features"], - dd["test_labels"], - dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], - dd["test_labels"], - dd["test_weights"]) + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + (dd["test_features"], + dd["test_labels"], + dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], + dd["test_labels"], + dd["test_weights"]) logger.info( f'Training model on {len(dk.data_dictionary["train_features"].columns)}' diff --git a/freqtrade/freqai/base_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py index e536efea3..0a6100df3 100644 --- a/freqtrade/freqai/base_models/BaseClassifierModel.py +++ b/freqtrade/freqai/base_models/BaseClassifierModel.py @@ -61,11 +61,12 @@ class BaseClassifierModel(IFreqaiModel): dd["train_labels"], dd["train_weights"]) - (dd["test_features"], - dd["test_labels"], - dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], - dd["test_labels"], - dd["test_weights"]) + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + (dd["test_features"], + dd["test_labels"], + dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], + dd["test_labels"], + dd["test_weights"]) logger.info( f"Training model on {len(dk.data_dictionary['train_features'].columns)} features" diff --git a/freqtrade/freqai/base_models/BasePyTorchClassifier.py b/freqtrade/freqai/base_models/BasePyTorchClassifier.py index 57f31629a..8a4e15308 100644 --- a/freqtrade/freqai/base_models/BasePyTorchClassifier.py +++ b/freqtrade/freqai/base_models/BasePyTorchClassifier.py @@ -197,11 +197,12 @@ class BasePyTorchClassifier(BasePyTorchModel): dd["train_labels"], dd["train_weights"]) - (dd["test_features"], - dd["test_labels"], - dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], - dd["test_labels"], - dd["test_weights"]) + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + (dd["test_features"], + dd["test_labels"], + dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], + dd["test_labels"], + dd["test_weights"]) logger.info( f"Training model on {len(dk.data_dictionary['train_features'].columns)} features" diff --git a/freqtrade/freqai/base_models/BasePyTorchRegressor.py b/freqtrade/freqai/base_models/BasePyTorchRegressor.py index b77fec31a..325743134 100644 --- a/freqtrade/freqai/base_models/BasePyTorchRegressor.py +++ b/freqtrade/freqai/base_models/BasePyTorchRegressor.py @@ -96,12 +96,15 @@ class BasePyTorchRegressor(BasePyTorchModel): dd["train_weights"]) = dk.feature_pipeline.fit_transform(dd["train_features"], dd["train_labels"], dd["train_weights"]) + dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"]) - (dd["test_features"], - dd["test_labels"], - dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], - dd["test_labels"], - dd["test_weights"]) + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + (dd["test_features"], + dd["test_labels"], + dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], + dd["test_labels"], + dd["test_weights"]) + dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"]) logger.info( f"Training model on {len(dk.data_dictionary['train_features'].columns)} features" diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py index 3cce978b5..2e07d3fb7 100644 --- a/freqtrade/freqai/base_models/BaseRegressionModel.py +++ b/freqtrade/freqai/base_models/BaseRegressionModel.py @@ -60,15 +60,15 @@ class BaseRegressionModel(IFreqaiModel): dd["train_weights"]) = dk.feature_pipeline.fit_transform(dd["train_features"], dd["train_labels"], dd["train_weights"]) - - (dd["test_features"], - dd["test_labels"], - dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], - dd["test_labels"], - dd["test_weights"]) - dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"]) - dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"]) + + if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) != 0: + (dd["test_features"], + dd["test_labels"], + dd["test_weights"]) = dk.feature_pipeline.transform(dd["test_features"], + dd["test_labels"], + dd["test_weights"]) + dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"]) logger.info( f"Training model on {len(dk.data_dictionary['train_features'].columns)} features"