title: How to forecast one step ahead with a scaled model
body: <p>I have correctly implemented a ML model for forecasting; I firstly <strong>scaled</strong> all the input features.</p>
  
  <p>Is it all right to <strong>train</strong> a model with <strong>scaled</strong> features and provide <strong>non-scaled</strong> ones to predict <strong>one-step</strong> ahead, using that model?</p>
  
  <p>For instance, having already trained a model with scaled features:</p>
  
  <pre><code>today_s_input_variables = np.array([[159, 500000, 6]])
  today_s_prediction = model.predict(today_s_input_variables)
  </code></pre>