KendallHeuristic: Feature-clustering based on Kendall Correlation Test.

In D2MCS: Data Driving Multiple Classifier System

Feature-clustering based on Kendall Correlation Test.

Description

Performs the feature-clustering using Kendall correlation tests.

Details

The method estimate the association between paired samples and compute a test of the value being zero. They use different measures of association, all in the range [-1, 1] with 0 indicating no association. Method valid only for bi-class problems.

Super class

D2MCS::GenericHeuristic -> KendallHeuristic

Methods

Public methods

• KendallHeuristic$new()

• KendallHeuristic$heuristic()

• KendallHeuristic$clone()

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Method new()

Empty function used to initialize the object arguments in runtime.

Usage

KendallHeuristic$new()

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Method heuristic()

Test for association between paired samples using Kendall's tau value.

Usage

KendallHeuristic$heuristic(col1, col2, column.names = NULL)

Arguments

col1

A numeric vector or matrix required to perform the clustering operation.

col2

A numeric vector or matrix to perform the clustering operation.

column.names

An optional character vector with the names of both columns.

Returns

a numeric vector of length 1 or NA if an error occurs.

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Method clone()

The objects of this class are cloneable with this method.

Usage

KendallHeuristic$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Dataset, cor.test

D2MCS documentation built on Aug. 23, 2022, 5:07 p.m.