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Make model_training_parameters optional

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Emre 2022-12-05 14:54:42 +03:00
parent b0f430b5ac
commit e734b39929
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4 changed files with 8 additions and 14 deletions
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4
config_examples/config_freqai.example.json
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@ -79,9 +79,7 @@
"test_size": 0.33, "test_size": 0.33,
"random_state": 1 "random_state": 1
}, },
"model_training_parameters": { "model_training_parameters": {}
"n_estimators": 1000
}
}, },
"bot_name": "", "bot_name": "",
"force_entry_enable": true, "force_entry_enable": true,

5
docs/freqai-configuration.md
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@ -26,10 +26,7 @@ FreqAI is configured through the typical [Freqtrade config file](configuration.m
}, },
"data_split_parameters" : { "data_split_parameters" : {
"test_size": 0.25 "test_size": 0.25
}, }
"model_training_parameters" : {
"n_estimators": 100
},
} }
``` ```

5
freqtrade/constants.py
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@ -608,9 +608,8 @@ CONF_SCHEMA = {
"backtest_period_days", "backtest_period_days",
"identifier", "identifier",
"feature_parameters", "feature_parameters",
"data_split_parameters", "data_split_parameters"
"model_training_parameters" ]
]
}, },
}, },
} }

2
freqtrade/freqai/prediction_models/ReinforcementLearner.py
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@ -61,7 +61,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs, model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
tensorboard_log=Path( tensorboard_log=Path(
dk.full_path / "tensorboard" / dk.pair.split('/')[0]), dk.full_path / "tensorboard" / dk.pair.split('/')[0]),
**self.freqai_info['model_training_parameters'] **self.freqai_info.get('model_training_parameters', {})
) )
else: else:
logger.info('Continual training activated - starting training from previously ' logger.info('Continual training activated - starting training from previously '