title: Text Classification using Pre-trained Word vectors without a neural network
body: <p>Background: I have been evaluating a variety of text classification methods on my dataset, including using feature vectors derived from word counts and TF-IDF, and then running these through various classifiers. My dataset is very small (about 2300 sentences and about 5 classes), and considering the above approaches treat different ones as completely separate, would like to use a word vector approach to classification. I have used pretrained word vectors with a shallow NN with little success.</p>
  
  <p>Problem: I am looking for an alternative method of using word vectors to classify my sentences and have thought of taking the word vectors for a sentence, combining them into a single vector, then taking the centroid of each class of sentence vectors - classification would then happen via a distance measure between a new sentence and the centroid.</p>
  
  <p>How can I combine the word vectors into a "sentence vector" given my small dataset?</p>