remove model_list

app.py

@@ -148,7 +148,7 @@ def compute_coherence_values_base_lda(dictionary, corpus, texts, limit, coherenc
         coherencemodel = CoherenceModel(model=model, texts=texts, dictionary=dictionary, coherence=coherence)
         coherence_values.append(coherencemodel.get_coherence())
 
-    return model_list, coherence_values
+    return coherence_values
 
 def compute_coherence_values2(corpus, dictionary, k, a, b):
     lda_model = gensim.models.ldamodel.LdaModel(corpus=corpus,
@@ -275,14 +275,13 @@ def full_lda(df):
         training_corpus = corpus_split
         training_corpus.remove(training_corpus[i])
         # print(training_corpus[i])
-        model_list, coherence_values = compute_coherence_values_base_lda(dictionary=id2word, 
+        coherence_values = compute_coherence_values_base_lda(dictionary=id2word, 
                                                             corpus=training_corpus,
                                                             texts=df['lemma_tokens'],
                                                             start=2,
                                                             limit=10,
                                                             step=1,
                                                             coherence='c_v')
-        # print(model_list + str(i))
         # print(coherence_values + str(i))
         for j in range(len(coherence_values)):
             coherence_averages[j] += coherence_values[j]