title: How to do Text classification using word2vec
body: <p>I want to perform text classification using word2vec.
  I got vectors of words.</p>
  
  <pre><code>ls = []
  sentences = lines.split(".")
  for i in sentences:
      ls.append(i.split())
  model = Word2Vec(ls, min_count=1, size = 4)
  words = list(model.wv.vocab)
  print(words)
  vectors = []
  for word in words:
      vectors.append(model[word].tolist())
  data = np.array(vectors)
  data
  </code></pre>
  
  <p>output:</p>
  
  <pre><code>array([[ 0.00933912,  0.07960335, -0.04559333,  0.10600036],
         [ 0.10576613,  0.07267512, -0.10718666, -0.00804013],
         [ 0.09459028, -0.09901826, -0.07074171, -0.12022413],
         [-0.09893986,  0.01500741, -0.04796079, -0.04447284],
         [ 0.04403428, -0.07966098, -0.06460238, -0.07369237],
         [ 0.09352681, -0.03864434, -0.01743148,  0.11251986],.....])
  </code></pre>
  
  <p>How can i perform classification (product &amp; non product)?</p>