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This commit is contained in:
Matthias
2022-07-24 16:54:39 +02:00
parent 70b7a254af
commit 1885deb632
7 changed files with 17 additions and 23 deletions
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7
freqtrade/freqai/prediction_models/BaseRegressionModel.py
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@@ -32,10 +32,9 @@ class BaseRegressionModel(IFreqaiModel):
"""
Filter the training data and train a model to it. Train makes heavy use of the datakitchen
for storing, saving, loading, and analyzing the data.
:params:
:unfiltered_dataframe: Full dataframe for the current training period
:metadata: pair metadata from strategy.
:returns:
:param unfiltered_dataframe: Full dataframe for the current training period
:param metadata: pair metadata from strategy.
:return:
:model: Trained model which can be used to inference (self.predict)
"""

5
freqtrade/freqai/prediction_models/BaseTensorFlowModel.py
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@@ -31,9 +31,8 @@ class BaseTensorFlowModel(IFreqaiModel):
"""
Filter the training data and train a model to it. Train makes heavy use of the datakitchen
for storing, saving, loading, and analyzing the data.
:params:
:unfiltered_dataframe: Full dataframe for the current training period
:metadata: pair metadata from strategy.
:param unfiltered_dataframe: Full dataframe for the current training period
:param metadata: pair metadata from strategy.
:returns:
:model: Trained model which can be used to inference (self.predict)
"""

5
freqtrade/freqai/prediction_models/CatboostPredictionModel.py
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@@ -19,9 +19,8 @@ class CatboostPredictionModel(BaseRegressionModel):
def fit(self, data_dictionary: Dict) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
train_data = Pool(

5
freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
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@@ -20,9 +20,8 @@ class CatboostPredictionMultiModel(BaseRegressionModel):
def fit(self, data_dictionary: Dict) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
cbr = CatBoostRegressor(

5
freqtrade/freqai/prediction_models/LightGBMPredictionModel.py
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@@ -21,9 +21,8 @@ class LightGBMPredictionModel(BaseRegressionModel):
Most regressors use the same function names and arguments e.g. user
can drop in LGBMRegressor in place of CatBoostRegressor and all data
management will be properly handled by Freqai.
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"])

5
freqtrade/freqai/prediction_models/LightGBMPredictionMultiModel.py
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@@ -20,9 +20,8 @@ class LightGBMPredictionMultiModel(BaseRegressionModel):
def fit(self, data_dictionary: Dict) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
lgb = LGBMRegressor(**self.model_training_parameters)