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Revision 7cc02d716432c352c7ac0663cfe368c24a1505bd authored by awojna on 06 February 2018, 16:05:04 UTC, committed by awojna on 06 February 2018, 16:05:04 UTC
Script description updated in make-pkg.sh
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Generate software citation in BibTex format (requires biblatex-software package)
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Generate software citation in BibTex format (requires biblatex-software package)
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Generate software citation in BibTex format (requires biblatex-software package)
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Description.props
# Description file of Rseslib package for Weka
#
#

# Package name (required)
PackageName=Rseslib

# Version (required)
Version=3.1.2

#Date
Date=2017-09-21

# Title (required)
Title=Rough Sets and Analogy-Based Reasoning

Category=Classification

# Author (required)
Author=Arkadiusz Wojna,Grzegorz Gora,Marcin Jalmuzna,Michal Kurzydlowski,Rafal Latkowski,Dariusz Ogorek,Marcin Piliszczuk,Beata Zielosko

# Maintainer (required)
Maintainer=Arkadiusz Wojna <wojna@mimuw.edu.pl>

# License (required)
License=GPL 3.0

# Description (required)
Description=The package provides 3 classifiers. Rule classifier based on rough sets uses the concepts of discernibility matrix, reducts and rules generated from reducts. \
It provides variety of algorithms generating reducts including faster for larger data sets local reducts and has modes to work with incomplete data and inconsistent data. \
K nearest neighbours classifier provides variety of distance measures that can work also for data with both numeric and nominal attributes and has built-in k optimization. \
It implements fast neighbours searching algorithm making the classifier work for very large data sets. The classifier has also the mode to work as RIONA algorithm. \
The third classifier is the extension of k nearest neighbours method that induces local metric for each classified object. \
It is dedicated rather to large data sets (2000+ training instances) and improves accuracy particularly in case of data containing nominal attributes.

# Package URL for obtaining the package archive (required)
PackageURL=http://rseslib.mimuw.edu.pl/weka/Rseslib3.1.2.zip

# URL for further information
URL=http://rseslib.mimuw.edu.pl

# Dependencies
Depends=weka (>=3.8.0)
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