[WIP] Introduce loss function argument for AADForest

Author: matwey

src/coniferest/aadforest.py

@@ -176,6 +176,10 @@ class AADForest(Coniferest):
     map_value : ["const", "exponential", "linear", "reciprocal"] or callable, optional
         An function applied to the leaf depth before weighting. Possible
         meaning variants are: 1, 1-exp(-x), x, -1/x.
+
+    loss : ["hinge"], optional (default="hinge")
+        Loss function used to optimize the leaf weights. The default is the hinge loss,
+        as in the original paper.
     """
 
     def __init__(
@@ -190,6 +194,7 @@ def __init__(
         random_seed=None,
         sampletrees_per_batch=1 << 20,
         map_value=None,
+        loss="hinge",
     ):
         super().__init__(
             trees=[],
@@ -231,6 +236,13 @@ def __init__(
         else:
             raise ValueError(f"map_value is neither a callable nor one of {', '.join(MAP_VALUES.keys())}.")
 
+        LOSSES = ["hinge"]
+
+        if loss not in LOSSES:
+            raise ValueError(f"loss is not one of {', '.join(LOSSES)}.")
+
+        self.loss = loss
+
         self.evaluator = None
 
     def _build_trees(self, data):