add classifier, improve model naming scheme

freqtrade/freqai/prediction_models/LightGBMRegressor.py

@@ -0,0 +1,39 @@
+import logging
+from typing import Any, Dict
+
+from lightgbm import LGBMRegressor
+
+from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
+
+
+logger = logging.getLogger(__name__)
+
+
+class LightGBMRegressor(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.
+        :param data_dictionary: the dictionary constructed by DataHandler to hold
+                                all the training and test data/labels.
+        """
+
+        if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0:
+            eval_set = None
+        else:
+            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