title: Combining Word vectors and Scalar Features for classification
body: <p>I am working on a short sentence classification problem where I get the following information </p>
  
  <p><strong>Input</strong>
  Age of the person (1-100)
  Gender of the person (Male or Female)
  Content of the sentence</p>
  
  <p><strong>Output</strong>
  Label (Type of Content)</p>
  
  <p>To model the sentences I'm using word2vec combined with tfidf. I would also like to add age and gender as features along with the sentence embedding to the classifier. What is the correct way to do this ? Since the embedding is an n-dimensional array and age,gender are scalars. I'm confused about how to add them and visualise the data. </p>