title: One-Hot Encoding on data Destroys Model?
body: <p>I have a feature in my data that represents different types of accounts (it's basically numbers, like 15, 2, 40, etc...).
  I decided to use one-hot encoding on that column using get_dummies().</p>
  
  <p>The model is handling a fraud detection problem, so i have approximately 1% of the data which is fraud.
  Before performing one-hot, the model is capable of predicting some fraud.
  After the one-hot - it predicts nothing. 0.</p>
  
  <p>I assume it's because of the one-hot encoding - it produces many features, and it might be not productive.</p>
  
  <p>Does that make sense? What can I do in that case?
  Thanks!</p>