Linear Discriminant Analysis Compute

This node performs Linear Discriminant Analysis (LDA) which is a dimensionality reduction technique. It takes class information into account in order to project the data into a space in which classes are well separated. The results are similar to Principle Component Analysis (PCA) and may be used in subsequent classification.

Options

Class column
Column containing class information.
Column selection
Columns containing the input data.
Fail if missing values are encountered
If checked, execution fails when the selected columns contain missing values. Otherwise, rows containing missing values are ignored during computation.

Input Ports

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Input table containing numeric columns and one column with class information.

Output Ports

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The intra-class scatter matrix.
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The inter-class scatter matrix.
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Table containing the spectral decomposition. Rows are in descending order according to eigenvalues (first column).
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Model holding the LDA transformation used by the Linear Discriminant Analysis Apply node to apply the transformation to, e.g. another validation set.

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