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2019 | OriginalPaper | Buchkapitel

Rseslib 3: Library of Rough Set and Machine Learning Methods with Extensible Architecture

verfasst von : Arkadiusz Wojna, Rafał Latkowski

Erschienen in: Transactions on Rough Sets XXI

Verlag: Springer Berlin Heidelberg

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Abstract

The paper presents a new generation of Rseslib library - a collection of rough set and machine learning algorithms and data structures in Java. It provides algorithms for discretization, discernibility matrix, reducts, decision rules and for other concepts of rough set theory and other data mining methods. The third version was implemented from scratch and in contrast to its predecessor it is available as a separate open-source library with API and with modular architecture aimed at high reusability and substitutability of its components. The new version can be used within Weka and with a dedicated graphical interface. Computations in Rseslib 3 can be also distributed over a network of computers.

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Metadaten
Titel
Rseslib 3: Library of Rough Set and Machine Learning Methods with Extensible Architecture
verfasst von
Arkadiusz Wojna
Rafał Latkowski
Copyright-Jahr
2019
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-58768-3_7

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