add inverse link function

Author: floriankozikowski

skglm/datafits/group.py

@@ -184,6 +184,10 @@ class PoissonGroup(Poisson):
     def __init__(self, grp_ptr, grp_indices):
         self.grp_ptr, self.grp_indices = grp_ptr, grp_indices
 
+    @staticmethod
+    def inverse_link(x):
+        return np.exp(x)
+
     def get_spec(self):
         return (
             ('grp_ptr', int32[:]),

skglm/datafits/single_task.py

@@ -590,6 +590,10 @@ class Poisson(BaseDatafit):
     def __init__(self):
         pass
 
+    @staticmethod
+    def inverse_link(x):
+        return np.exp(x)
+
     def get_spec(self):
         pass
 
@@ -664,6 +668,10 @@ class Gamma(BaseDatafit):
     def __init__(self):
         pass
 
+    @staticmethod
+    def inverse_link(x):
+        return np.exp(x)
+
     def get_spec(self):
         pass
 

skglm/estimators.py

@@ -19,7 +19,7 @@
 
 from skglm.solvers import AndersonCD, MultiTaskBCD, GroupBCD, ProxNewton, LBFGS
 from skglm.datafits import (
-    Cox, Quadratic, Logistic, Poisson, PoissonGroup, Gamma, QuadraticSVC,
+    Cox, Quadratic, Logistic, QuadraticSVC,
     QuadraticMultiTask, QuadraticGroup,)
 from skglm.penalties import (L1, WeightedL1, L1_plus_L2, L2, WeightedGroupL2,
                              MCPenalty, WeightedMCPenalty, IndicatorBox, L2_1)
@@ -266,8 +266,8 @@ def predict(self, X):
             else:
                 indices = scores.argmax(axis=1)
             return self.classes_[indices]
-        elif isinstance(self.datafit, (Poisson, PoissonGroup, Gamma)):
-            return np.exp(self._decision_function(X))
+        elif hasattr(self.datafit, "inverse_link"):
+            return self.datafit.inverse_link(self._decision_function(X))
         else:
             return self._decision_function(X)