make model deterministic and fix server errors

Author: carlcortright

__pycache__/trainModel.cpython-37.pyc

@@ -1,13 +1,15 @@
 from utils import *
 from gensim import corpora, models
+import numpy as np
 
 def train_model(data):
+    # Stabilizes the model so the results are deterministic
+    np.random.seed(42)
     # Load our data into a dataframe and preprocess the text
     df = data_to_pd(data)
     corpus = df['text'].map(preprocess)
     # Creates a dictionary of words from the corpus
     dictionary = gensim.corpora.Dictionary(corpus)
-    dictionary.filter_extremes(no_below=15, no_above=0.5, keep_n=100000)
     bow_corpus = [dictionary.doc2bow(doc) for doc in corpus]
     # Train our model
     lda_model = gensim.models.LdaMulticore(bow_corpus, num_topics=3, id2word=dictionary, passes=2, workers=2)
@@ -16,6 +18,7 @@ def train_model(data):
 def classify_search(search, dictionary, lda_model):
     bow_vector = dictionary.doc2bow(preprocess(search))
     ranked = sorted(lda_model[bow_vector], key=lambda tup: -1*tup[1])
+    print(ranked)
     return ranked[0][0]
 
 def partition(data, search):
@@ -28,4 +31,4 @@ def partition(data, search):
             scores.append(True)
         else:
             scores.append(False)
-    return scores
+    return scores