Title
Rseslib 3: Library of Rough Set and Machine Learning Methods with Extensible Architecture.
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.
Year
DOI
Venue
2019
10.1007/978-3-662-58768-3_7
T. Rough Sets
Field
DocType
Volume
Decision rule,Data structure,Reduct,Computer science,Rough set,Graphical user interface,Artificial intelligence,Java,Reusability,Machine learning,Computation
Journal
21
Citations 
PageRank 
References 
1
0.34
14
Authors
2
Name
Order
Citations
PageRank
Arkadiusz Wojna118312.82
Rafal Latkowski2222.33