Uses of Class
deepnetts.data.norm.AbstractScaler

Packages that use AbstractScaler

Package	Description
deepnetts.data.norm	Data normalization methods, used to scale data to specific range, in order to make them suitable for use by a neural network.
deepnetts.net	Neural network architectures with their corresponding builders.

Uses of AbstractScaler in deepnetts.data.norm

Subclasses of AbstractScaler in deepnetts.data.norm

Modifier and Type	Class and Description
class	DecimalScaler Decimal scale normalization for the given data set.
class	MaxScaler Performs max normalization, rescales data to corresponding max value in each column.
class	MinMaxScaler Performs Min Max normalization on the given data set.
class	RangeScaler Normalize data set to specified range.
class	Standardizer Performs standardization on inputs in order to get desired statistical properties of the data set (zero mean and one standard deviation).

Uses of AbstractScaler in deepnetts.net

Methods in deepnetts.net that return AbstractScaler

Modifier and Type	Method and Description
AbstractScaler	NeuralNetwork.getNormalizer() Returns data normalization method that is applied to network's inputs.

Methods in deepnetts.net with parameters of type AbstractScaler

Modifier and Type	Method and Description
void	NeuralNetwork.setNormalizer(AbstractScaler normalizer) Sets normalization data normalization method that is applied to network's inputs.