IndependentComponentAnalysis Properties |
The IndependentComponentAnalysis type exposes the following members.
Name | Description | |
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Algorithm |
Gets or sets the
FastICA algorithm used by the analysis.
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Components |
Gets the Independent Components in a object-oriented structure.
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Contrast |
Gets or sets the
Contrast function to be used by the analysis.
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DemixingMatrix |
Gets a matrix containing the demixing coefficients for
the original source data being analyzed. Each column
corresponds to an independent component.
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Iterations |
Gets or sets the maximum number of iterations
to perform. If zero, the method will run until
convergence.
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Means |
Gets the column means of the original data.
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Method |
Gets or sets the normalization method used for this analysis.
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MixingMatrix |
Gets a matrix containing the mixing coefficients for
the original source data being analyzed. Each column
corresponds to an independent component.
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NumberOfInputs |
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) | |
NumberOfOutputs |
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) | |
Overwrite |
Gets or sets whether calculations will be performed overwriting
data in the original source matrix, using less memory.
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ParallelOptions |
Gets or sets the parallelization options for this algorithm.
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Result | Obsolete.
Gets the resulting projection of the source
data given on the creation of the analysis
into the space spawned by independent components.
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Source | Obsolete.
Source data used in the analysis.
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StandardDeviation |
Gets the column standard deviations of the original data.
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Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
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Tolerance |
Gets or sets the maximum absolute change in
parameters between iterations that determine
convergence.
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WhiteningMatrix |
Gets the whitening matrix used to transform
the original data to have unit variance.
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