ResIndex: Generate Simple yet Effective Metric of Feature Importance for Classification Problems

An intuitive and explainable metric of Feature Importance for Classification Problems. Resolution Index measures the extent to which a Feature clusters different classes when data is sorted on it. User provides a DataFrame, column name of the Class, sample size and number of iterations used for calculation. Resolution Index for each Feature is returned, which can be effectively used to rank Features and reduce Dimensionality of Training data. For more details on Feature Selection see Theng and Bhoyar (2023) <doi:10.1007/s10115-023-02010-5>.

Version:	0.1.0
Published:	2025-03-18
DOI:	10.32614/CRAN.package.ResIndex
Author:	Anand Jha [aut, cre]
Maintainer:	Anand Jha <anandorjha18 at gmail.com>
License:	LGPL-2
NeedsCompilation:	no
CRAN checks:	ResIndex results

Documentation:

Reference manual:

ResIndex.html , ResIndex.pdf

Downloads:

Package source:	ResIndex_0.1.0.tar.gz
Windows binaries:	r-devel: ResIndex_0.1.0.zip, r-release: ResIndex_0.1.0.zip, r-oldrel: ResIndex_0.1.0.zip
macOS binaries:	r-release (arm64): ResIndex_0.1.0.tgz, r-oldrel (arm64): ResIndex_0.1.0.tgz, r-release (x86_64): ResIndex_0.1.0.tgz, r-oldrel (x86_64): ResIndex_0.1.0.tgz

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