Package 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.

See: Description

Class Summary

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

Package deepnetts.data.norm Description

Data normalization methods, used to scale data to specific range, in order to make them suitable for use by a neural network.