fix binary-classification

data/model/binary-classification.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9570c076603ee591b4bdf5aee6fd033b87ba757f9438a45ce3171a880a871a39
-size 204632
+oid sha256:82b3dbcc96b85747d1dac74332dd09544f72bf4d0699aae158cabbd61610c3bb
+size 1762032

modules/binary_classification.py

@@ -55,7 +55,7 @@ def predict_sentiment(review, vocab, tokenizer, model):
     # convert to line
     line = ' '.join(tokens)
     # encode
-    encoded = tokenizer.texts_to_matrix([line], mode='tfidf')
+    encoded = tokenizer.texts_to_matrix([line], mode='freq')
     # predict sentiment
     yhat = model.predict(encoded, verbose=0)
     # retrieve predicted percentage and label
@@ -89,11 +89,11 @@ def binary_classification(text):
 	positive = 0
 	negative = 0
 	if(sentiment == 'POSITIVE'):
-		positive = percent
-		negative = 100 - percent.astype(float)
+		positive = percent.astype(float) * 100
+		negative = 100 - positive
 	else:
-		negative = percent
-		positive = 100 - percent.astype(float)
+		negative = percent.astype(float) * 100
+		positive = 100 - negative
 	labels = {
         'positive' : "%.2f" % float(positive/100),
         'negative' : "%.2f" % float(negative/100)