remove calls to loss from problem.py

This will break lexicase but also allow X_protected to be passed until @shakiba-shb fixes `metrics.loss()`

fomo/problem.py

@@ -94,9 +94,6 @@ def _evaluate(self, sample_weight, out, *args, **kwargs):
             j += 1
 
         out['F'] = np.asarray(f)
-        fn, fng = metrics.loss(est, X, y, 'FNR', **self.metric_kwargs)
-        out['fn'] = fn #FNR of all samples
-        out['fng'] = fng #FNR of each group
 
 class SurrogateProblem(ElementwiseProblem):
     """ The evaluation function for each candidate weights. 
@@ -175,9 +172,6 @@ def _evaluate(self, x, out, *args, **kwargs):
             j += 1
 
         out['F'] = np.asarray(f)
-        fn, fng = metrics.loss(est, X, y, 'FNR', **self.metric_kwargs)
-        out['fn'] = fn #FNR of all samples
-        out['fng'] = fng #FNR of every group
 
 class MLPProblem(SurrogateProblem):
     """ The evaluation function for each candidate weights. 
@@ -198,4 +192,4 @@ class InterLinearProblem(SurrogateProblem):
 
     """
     def _get_surrogate(self):
-        return InterLinear(self.X_protected)
+        return InterLinear(self.X_protected)