information.gain: Entropy-based filters

Description Usage Arguments Details Value Author(s) Examples

Description

The algorithms find weights of discrete attributes basing on their correlation with continous class attribute.

Usage

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Arguments

formula

A symbolic description of a model.

data

Data to process.

unit

Unit for computing entropy (passed to entropy. Default is "log".

Details

information.gain is

H(Class) + H(Attribute) - H(Class, Attribute)

.

gain.ratio is

(H(Class) + H(Attribute) - H(Class, Attribute)) / H(Attribute)

symmetrical.uncertainty is

2 * (H(Class) + H(Attribute) - H(Class, Attribute)) / (H(Attribute) + H(Class))

Value

a data.frame containing the worth of attributes in the first column and their names as row names

Author(s)

Piotr Romanski, Lars Kotthoff

Examples

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Najah-lshanableh/R-data-mining documentation built on May 6, 2019, 10:11 a.m.