Refactor and fix unbiasing

app.py

@@ -30,12 +30,17 @@ def get_interesting_probs(probs, intr_threshold):
 def unbias(p):
     return (2 * p) / (p + 1)
 
-def unbias_or_noop(p, noop=False):
-    return unbias(p) if not noop else p
-
 def predict_bayes(text, intr_threshold, unbiased=False):
     words = tokenize(text)
-    probs = [unbias_or_noop(model_probs.get(w, model_probs[UNK]), noop=not unbiased) for w in words]
+    probs = []
+    for w in words:
+        try:
+            p = model_probs[w]
+            if unbiased:
+                p = unbias(p)
+        except KeyError:
+            p = model_probs[UNK]
+        probs.append(p)
     interesting_probs = get_interesting_probs(probs, intr_threshold)
     return combine(interesting_probs)