Normalization provides a basic framework for mapping input values to specific value ranges, usually the numeric range
[0 .. 1]. Normalization is used, e.g., in neural networks and clustering models.
Defines how to normalize an input field by piecewise linear interpolation. The mapMissingTo attribute defines the
value the output is to take if the input is missing. If the mapMissingTo attribute is not specified, then missing
input values produce a missing result.
Normalization provides a basic framework for mapping input values to specific value ranges, usually the numeric range [0 .. 1]. Normalization is used, e.g., in neural networks and clustering models.
Defines how to normalize an input field by piecewise linear interpolation. The mapMissingTo attribute defines the value the output is to take if the input is missing. If the mapMissingTo attribute is not specified, then missing input values produce a missing result.