title: XGBoost use 3-Dimensional Input Containing Time Steps in Python?
body: <p>I am trying to train a <code>XGBRegressor</code> on time series data reshaped to have time steps, so the resulting shape of <code>X_train</code> can be something like <code>(12345, 5, 10)</code> if there are 12345 samples, 10 features and a time step of 5.</p>
  
  <p>However, when we try to train <code>XGBRegressor</code> using such a training data,</p>
  
  <pre><code>import xgboost as xgb
  xgb = xgb.XGBRegressor()
  xgbr.fit(X_train, y_train)
  </code></pre>
  
  <p>we get the error</p>
  
  <blockquote>
    <p>ValueError: ('Expecting 2 dimensional numpy.ndarray, got: ', (12345, 5, 10))</p>
  </blockquote>
  
  <p>What is the correct way of training <code>XGBRegressor</code> on training data containing time steps?</p>