add LightGBMPredictionMultiModel

This commit is contained in:
robcaulk 2022-07-22 12:40:51 +02:00
parent afcb0bec00
commit 98c8a447b2

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import logging
from typing import Any, Dict
from lightgbm import LGBMRegressor
from sklearn.multioutput import MultiOutputRegressor
from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
logger = logging.getLogger(__name__)
class LightGBMPredictionMultiModel(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:
"""
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.
"""
lgb = LGBMRegressor(**self.model_training_parameters)
X = data_dictionary["train_features"]
y = data_dictionary["train_labels"]
eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"])
sample_weight = data_dictionary["train_weights"]
model = MultiOutputRegressor(estimator=lgb)
model.fit(X=X, y=y, sample_weight=sample_weight) # , eval_set=eval_set)
train_score = model.score(X, y)
test_score = model.score(*eval_set)
logger.info(f"Train score {train_score}, Test score {test_score}")
return model