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Class Summary |
| AbstractFeatureTransformation |
Abstract super class of all operators transforming the feature space. |
| DimensionalityReducer |
Abstract class representing some common functionality of dimensionality reduction methods. |
| DimensionalityReducerModel |
The model for the generic dimensionality reducer. |
| Eigenvector |
This class holds information about one eigenvector and eigenvalue. |
| EigenvectorModelVisualization |
This class can be used for all eigenvector based model visualizations. |
| 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. |
| 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. |
| JamaDimensionalityReduction |
This class represents an abstract framework for performing dimensionality reduction using the JAMA package. |
| KernelPCA |
This operator performs a kernel-based principal components analysis (PCA). |
| KernelPCAModel |
The model for the Kernel-PCA. |
| 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). |
| SOMDimensionalityReductionModel |
The model for the SOM dimensionality reduction. |
| SVDReduction |
A dimensionality reduction method based on Singular Value Decomposition. |
| WeightVector |
This class holds information about one eigenvector and eigenvalue. |