Package edu.udo.cs.yale.operator.features.transformation

Provides operators for feature space transformations like PCA or ICA.

See:
Description

Interface Summary

ComponentWeightsCreatable

This is an interface for models holding several components for feature transformation.

Class Summary

FastICA	This operator performs the independent componente analysis (ICA).
FastICAModel	This is the transformation model of the FastICA.
FourierTransform	Creates a new example set consisting of the result of a fourier transformation for each attribute of the input example set.
FunctionValueSeries	Calculates for each sample a series of function values.
GHA	Generalized Hebbian Algorithm (GHA) is an iterative method to compute principal components.
GHAModel	This is the transformation model of the GHA The number of components is initially specified by the GHA.
HyperplaneProjection	Projects the examples onto the hyperplane using AttributeWeights as the normal.
PCA	This operator performs a principal components analysis (PCA) using the covariance matrix.
PCAModel	This is the transformation model of the principal components analysis.
PrincipalComponentsTransformation	Builds the principal components of the given data.
SOMDimensionalityReduction	This operator performs a dimensionality reduction based on a SOM (Self Organizing Map, aka Kohonen net).
SplitSVMModel	Splits a JMySVMModel into an ExampleSet of the support vectors and AttributeWeights representing the normal of the hyperplane.

Package edu.udo.cs.yale.operator.features.transformation Description

Provides operators for feature space transformations like PCA or ICA.