add continual learning to catboost and friends

freqtrade/freqai/prediction_models/LightGBMClassifier.py

@@ -4,7 +4,7 @@ from typing import Any, Dict
 from lightgbm import LGBMClassifier
 
 from freqtrade.freqai.prediction_models.BaseClassifierModel import BaseClassifierModel
-
+from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
 
 logger = logging.getLogger(__name__)
 
@@ -16,7 +16,7 @@ class LightGBMClassifier(BaseClassifierModel):
     has its own DataHandler where data is held, saved, loaded, and managed.
     """
 
-    def fit(self, data_dictionary: Dict) -> Any:
+    def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen) -> Any:
         """
         User sets up the training and test data to fit their desired model here
         :params:
@@ -35,9 +35,14 @@ class LightGBMClassifier(BaseClassifierModel):
         y = data_dictionary["train_labels"].to_numpy()[:, 0]
         train_weights = data_dictionary["train_weights"]
 
+        if dk.pair not in self.dd.model_dictionary or not self.continual_learning:
+            init_model = None
+        else:
+            init_model = self.dd.model_dictionary[dk.pair]
+
         model = LGBMClassifier(**self.model_training_parameters)
 
         model.fit(X=X, y=y, eval_set=eval_set, sample_weight=train_weights,
-                  eval_sample_weight=[test_weights])
+                  eval_sample_weight=[test_weights], init_model=init_model)
 
         return model