NeurEco performs the data normalization automatically for **Parametric Frequency Sweep**.

* for input features: a Min-Max normalization is performed by feature, meaning that each input feature :math:`f` is normalized independently from others, so that

  .. math:: f_{normalized}=\frac{f-min(f)}{max(f)}

* for output features: all features are normalized together by division by their maximum absolute value, so that

  .. math:: targets_{normalized}=\frac{targets}{max(|targets|)}