improve docs, update doc strings

docs/strategy_migration.md

@@ -736,7 +736,7 @@ If you have created your own custom `IFreqaiModel` with a custom `train()`/`pred
 
 The conversion involves first removing `data_cleaning_train/predict()` and replacing them with a `define_data_pipeline()` and `define_label_pipeline()` function to your `IFreqaiModel` class:
 
-```python  linenums="1" hl_lines="11-14 43-44 51-52"
+```python  linenums="1" hl_lines="11-14 47-49 55-57"
 class MyCoolFreqaiModel(BaseRegressionModel):
     """
     Some cool custom IFreqaiModel you made before Freqtrade version 2023.6
@@ -773,9 +773,13 @@ class MyCoolFreqaiModel(BaseRegressionModel):
         dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"])
         dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"])
 
+        # ... your custom code
+
+        return model
+
     def predict(
         self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs
-    ) -> Tuple[DataFrame, npt.NDArray[np.int_]]: # 37
+    ) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
 
         # ... your custom stuff
 
@@ -798,6 +802,9 @@ class MyCoolFreqaiModel(BaseRegressionModel):
         else:
             dk.DI_values = np.zeros(len(outliers.index))
         dk.do_predict = outliers.to_numpy()
+
+        # ... your custom code
+        return (pred_df, dk.do_predict)
 ```
 
 

freqtrade/freqai/base_models/BaseClassifierModel.py

@@ -17,8 +17,8 @@ logger = logging.getLogger(__name__)
 class BaseClassifierModel(IFreqaiModel):
     """
     Base class for regression type models (e.g. Catboost, LightGBM, XGboost etc.).
-    User *must* inherit from this class and set fit() and predict(). See example scripts
+    User *must* inherit from this class and set fit(). See example scripts
-    such as prediction_models/CatboostPredictionModel.py for guidance.
+    such as prediction_models/CatboostClassifier.py for guidance.
     """
 
     def train(

freqtrade/freqai/base_models/BaseRegressionModel.py

@@ -16,8 +16,8 @@ logger = logging.getLogger(__name__)
 class BaseRegressionModel(IFreqaiModel):
     """
     Base class for regression type models (e.g. Catboost, LightGBM, XGboost etc.).
-    User *must* inherit from this class and set fit() and predict(). See example scripts
+    User *must* inherit from this class and set fit(). See example scripts
-    such as prediction_models/CatboostPredictionModel.py for guidance.
+    such as prediction_models/CatboostRegressor.py for guidance.
     """
 
     def train(