Interface | Description |
---|---|
DataNormalization |
An interface for data normalizers.
|
MultiDataNormalization |
An interface for multi dataset normalizers.
|
Normalizer<T> |
Base interface for all normalizers
|
NormalizerStrategy<S extends NormalizerStats> |
Interface for strategies that can normalize and denormalize data arrays based on statistics of the population
|
Class | Description |
---|---|
AbstractDataSetNormalizer<S extends NormalizerStats> |
Abstract base class for normalizers
that act upon
DataSet instances
or iterators |
AbstractMultiDataSetNormalizer<S extends NormalizerStats> |
Abstract base class for normalizers that act upon
MultiDataSet instances or iterators |
AbstractNormalizer |
Abstract base class for normalizers for both DataSet and MultiDataSet processing
|
ImageFlatteningDataSetPreProcessor |
A DataSetPreProcessor used to flatten a 4d CNN features array to a flattened 2d format (for use in networks such
as a DenseLayer/multi-layer perceptron)
|
ImagePreProcessingScaler |
Created by susaneraly on 6/23/16.
|
MinMaxStrategy |
NormalizerStrategy implementation that will normalize and denormalize data arrays to a given range, based on
statistics of the upper and lower bounds of the population |
MultiNormalizerHybrid |
Pre processor for MultiDataSet that can be configured to use different normalization strategies for different inputs
and outputs, or none at all.
|
MultiNormalizerMinMaxScaler |
Pre processor for MultiDataSet that normalizes feature values (and optionally label values) to lie between a minimum
and maximum value (by default between 0 and 1)
|
MultiNormalizerStandardize |
Pre processor for MultiDataSet that normalizes feature values (and optionally label values) to have 0 mean and
a standard deviation of 1
|
NormalizerMinMaxScaler |
Pre processor for DataSets that normalizes feature values (and optionally label values) to lie between a minimum
and maximum value (by default between 0 and 1)
|
NormalizerStandardize |
Created by susaneraly, Ede Meijer
variance and mean
Pre processor for DataSet that normalizes feature values (and optionally label values) to have 0 mean and a standard
deviation of 1
|
StandardizeStrategy |
NormalizerStrategy implementation that will standardize and de-standardize data arrays, based on statistics
of the means and standard deviations of the population |
VGG16ImagePreProcessor |
This is a preprocessor specifically for VGG16.
|
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