X.gini

a distribution of values on the
  decision attribute.

decisionDistrib

It is an auxiliary function for the <code>qualityF</code>
parameter in the
<code><a href="/link/FS.greedy.heuristic.reduct.RST?package=RoughSets&version=1.1-0" rd-options="" data-mini-rdoc="RoughSets::FS.greedy.heuristic.reduct.RST">FS.greedy.heuristic.reduct.RST</a></code> and
<code><a href="/link/FS.greedy.heuristic.superreduct.RST?package=RoughSets&version=1.1-0" rd-options="" data-mini-rdoc="RoughSets::FS.greedy.heuristic.superreduct.RST">FS.greedy.heuristic.superreduct.RST</a></code>
functions. It is based on the <em>gini</em> index as a
measure of information (Stoffel and Raileanu, 2000).

This package provides comprehensive implementations of algorithms
    based on rough set theory (RST) and fuzzy rough set theory (FRST), and
    integrates these two theories into a single package. It provides
    implementations, not only for the basic concepts of RST and FRST, but also
    most common methods based on them for handling some: discretization,
    feature selection, instance selection, rule induction, and classification
    based on nearest neighbors. RST was introduced by Zdzislaw Pawlak in 1982
    as a sophisticated mathematical tool based on indiscernibility relations to
    model and process imprecise or incomplete information. It works on
    symbolic-valued datasets for tackling the data analysis problems. By using
    the indiscernibility relation for objects/instances, RST does not require
    additional parameters to analyze the data. FRST is an extension of RST. The
    FRST combines concepts of vagueness and indiscernibility that are expressed
    with fuzzy sets (as proposed by Zadeh, in 1965) and RST. In addition, we
    provide a new feature in this version which is missing value completion.
    Finally, our package should be considered as an alternative software
    library for analyzing data based on RST and FRST. Furthermore, in this
    version we provide some algorithms for dealing with missing values.

X.gini: The gini-index gain measure function

Description

Usage

Arguments

Value

References