mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-11 02:33:55 +00:00
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
|
import logging
|
||
|
from typing import Any, Dict
|
||
|
|
||
|
from catboost import CatBoostClassifier, Pool
|
||
|
|
||
|
from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
|
||
|
|
||
|
|
||
|
logger = logging.getLogger(__name__)
|
||
|
|
||
|
|
||
|
class CatboostClassifier(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.
|
||
|
"""
|
||
|
|
||
|
train_data = Pool(
|
||
|
data=data_dictionary["train_features"],
|
||
|
label=data_dictionary["train_labels"],
|
||
|
weight=data_dictionary["train_weights"],
|
||
|
)
|
||
|
|
||
|
cbr = CatBoostClassifier(
|
||
|
allow_writing_files=False,
|
||
|
loss_function='MultiClass',
|
||
|
**self.model_training_parameters,
|
||
|
)
|
||
|
|
||
|
cbr.fit(train_data)
|
||
|
|
||
|
return cbr
|