title: Is it theoretically reasonable to use CNN for data like categorical and numeric data?
body: <p>I'm trying to use CNN to do a binary classification.
  As CNN shows its strength in feature extraction, it has been many uses for pattern data like image and voice.
  However, the dataset I have is not image or voice data, but categorical data and numerical data, which are different from this case.
  My question is as follows.</p>
  <ol>
  <li><p>In this situation,  Is it theoretically reasonable to use CNN for data in this configuration?</p>
  </li>
  <li><p>If it is reasonable, would it be reasonable to artificially place my dataset in a two-dimensional form and perform a 2D-CNN?</p>
  </li>
  </ol>
  <p>I often see examples of using CNN in many classifiers through Kaggle and various media, and I can see not only images and voices, but also numerical and categorical data like mine.
  I really wonder this is theoretically a problem, and I would appreciate it if you could recommend it if you knew about the related paper or research.</p>
  <p>I'm looking forward to hearing any advice about this situation. Thank you for your answer.</p>