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Package

weka.attributeSelection

Synopsis

Performs latent semantic analysis and transformation of the data. Use in conjunction with a Ranker search. A low-rank approximation of the full data is found by either specifying the number of singular values to use or specifying a proportion of the singular values to cover.

Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (latentSemanticAnalysis).

Options

The table below describes the options available for LatentSemanticAnalysis.

Option

Description

maximumAttributeNames

The maximum number of attributes to include in transformed attribute names.

normalize

Normalize input data.

rank

Matrix rank to use for data reduction. Can be a proportion to indicate desired coverage

Capabilities

The table below describes the capabilites of LatentSemanticAnalysis.

Capability

Supported

Class

Date class, Numeric class, Binary class, Nominal class, Missing class values, No class

Attributes

Numeric attributes, Nominal attributes, Binary attributes, Missing values, Date attributes, Empty nominal attributes, Unary attributes

Min # of instances

1

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