feat(Metalearner): Implemented abstract base class for Metalearner

aucmedi/ensemble/metalearner/ml_base.py

@@ -28,12 +28,12 @@
 class Metalearner_Base(ABC):
     """ An abstract base class for a Metalearner class.
 
-    Metaleaner are similar to [aggregate functions][aucmedi.ensemble.aggregate],
-    however metaleaners are models which are trained before usage.
+    Metalearner are similar to [aggregate functions][aucmedi.ensemble.aggregate],
+    however Metalearners are models which are trained before usage.
 
-    Metaleaners are utilized in [Stacking][aucmedi.ensemble.stacking] pipelines.
+    Metalearners are utilized in [Stacking][aucmedi.ensemble.stacking] pipelines.
 
-    A Metaleaner act as combiner algorithm which is trained to make a final prediction
+    A Metalearner act as combiner algorithm which is trained to make a final prediction
     using predictions of the other algorithms (Neural_Networks) as inputs.
 
     ```
@@ -48,51 +48,47 @@ class Metalearner_Base(ABC):
     -> shape (1, 3)
     ```
 
-    ???+ example "Create a custom Metaleaner class"
-        ```python
-        from aucmedi.ensemble.aggregate.agg_base import Aggregate_Base
-
-        class My_custom_Aggregate(Aggregate_Base):
-            def __init__(self):                 # you can pass class variables here
-                pass
-
-            def aggregate(self, preds):
-                preds_combined = np.mean(preds, axis=0)     # do some combination operation
-                return preds_combined                       # return combined predictions
-        ```
-
     !!! info "Required Functions"
         | Function            | Description                                                |
         | ------------------- | ---------------------------------------------------------- |
         | `__init__()`        | Object creation function.                                  |
-        | `training()`        | Fit Metaleaner model.                                      |
+        | `training()`        | Fit Metalearner model.                                     |
         | `prediction()`      | Merge multiple class predictions into a single prediction. |
-        | `dump()`            | Store Metaleaner model to disk.                            |
-        | `load()`            | Load Metaleaner model from disk.                           |
+        | `dump()`            | Store Metalearner model to disk.                           |
+        | `load()`            | Load Metalearner model from disk.                          |
     """
     #---------------------------------------------#
     #                Initialization               #
     #---------------------------------------------#
     @abstractmethod
     def __init__(self):
-        """ Initialization function which will be called during the Aggregation object creation.
+        """ Initialization function which will be called during the Metalearner object creation.
 
-        This function can be used to pass variables and options in the Aggregation instance.
+        This function can be used to pass variables and options in the Metalearner instance.
         The are no mandatory required parameters for the initialization.
         """
         pass
 
     #---------------------------------------------#
     #                  Training                   #
     #---------------------------------------------#
-    def training(self, train_x, train_y):
+    @abstractmethod
+    def training(self, x, y):
+        """ Training function to fit the Metalearner model.
+
+        Args:
+            x (numpy.ndarray):          Ensembled predictions encoded in a NumPy Matrix with shape (N_models, N_classes).
+            y (numpy.ndarray):          Classification list with One-Hot Encoding. Provided by
+                                        [input_interface][aucmedi.data_processing.io_data.input_interface].
+        """
         pass
 
     #---------------------------------------------#
     #                  Prediction                 #
     #---------------------------------------------#
+    @abstractmethod
     def prediction(self, data):
-        """ Aggregate the image by merging multiple predictions into a single one.
+        """ Merge multiple predictions into a single one.
 
         It is required to return the merged predictions (as NumPy matrix).
         It is possible to pass configurations through the initialization function for this class.
@@ -107,11 +103,23 @@ def prediction(self, data):
     #---------------------------------------------#
     #              Dump Model to Disk             #
     #---------------------------------------------#
+    @abstractmethod
     def dump(self, path):
+        """ Store metalearner model to disk.
+
+        Args:
+            file_path (str):    Path to store the model on disk.
+        """
         pass
 
     #---------------------------------------------#
     #             Load Model from Disk            #
     #---------------------------------------------#
+    @abstractmethod
     def load(self, path):
+        """ Load metalearner model and its weights from a file.
+
+        Args:
+            file_path (str):            Input path, from which the model will be loaded.
+        """
         pass