stable/freqtrade/freqai/prediction_models/LightGBMPredictionModel.py

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import logging
from typing import Any, Dict
from lightgbm import LGBMRegressor
from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
logger = logging.getLogger(__name__)
class LightGBMPredictionModel(BaseRegressionModel):
"""
User created prediction model. The class needs to override three necessary
functions, predict(), train(), fit(). The class inherits ModelHandler which
has its own DataHandler where data is held, saved, loaded, and managed.
"""
def fit(self, data_dictionary: Dict) -> Any:
"""
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.
"""
eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"])
X = data_dictionary["train_features"]
y = data_dictionary["train_labels"]
model = LGBMRegressor(**self.model_training_parameters)
model.fit(X=X, y=y, eval_set=eval_set)
return model