Hands-On Machine Learning with C++

Normalizing with Shark-ML

The Shark-ML library implements several normalization approaches. They are implemented as trainer classes for the Normalizer model type. We can reuse the Normalizer type after training on different data. There are the following normalization trainer classes:

• NormalizeComponentsUnitInterval—This class trains a normalization model that transforms data to fit a unit interval.
• NormalizeComponentsUnitVariance—This class trains a normalization model that transforms data to have unit variance and, optionally, a zero mean.
• NormalizeComponentsWhitening—This class trains a normalization model that transforms data to have zero mean and unit variance by default, but we can specify the target variance value.

The following code ...