call alpha

multimodal/boosting/cumbo.py

@@ -216,10 +216,10 @@ class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
         """Compute values of confidence rate alpha given edge values."""
         np.where(edges > 1.0, edges, 1.0)
         alphas = 0.5 * np.log((1. + edges) / (1. - edges))
-        if np.any(np.isinf(alphas)) or np.any(np.isnan(alphas)):
-
-            alphas[np.where(np.isnan(alphas))[0]] = 1.0
+        if np.any(np.isinf(alphas)):
             alphas[np.where(np.isinf(alphas))[0]] = 1.0
+        if np.any(np.isnan(alphas)):
+            alphas[np.where(np.isnan(alphas))[0]] = 1.0
         return alphas
 
     def _compute_cost(self, label_score, predicted_classes, y, alphas, betas,

multimodal/boosting/mumbo.py

@@ -223,10 +223,10 @@ class MumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
         """Compute values of confidence rate alpha given edge values."""
         np.where(edges > 1.0, edges, 1.0)
         alphas = 0.5 * np.log((1. + edges) / (1. - edges))
-        if np.any(np.isinf(alphas)) or np.any(np.isnan(alphas)):
-
-            alphas[np.where(np.isnan(alphas))[0]] = 1.0
+        if np.any(np.isinf(alphas)):
             alphas[np.where(np.isinf(alphas))[0]] = 1.0
+        if np.any(np.isnan(alphas)):
+            alphas[np.where(np.isnan(alphas))[0]] = 1.0
         return alphas
 
     def _compute_cost_global(self, label_score_global, best_predicted_classes,