RSES is a toolkit for analysis of table data running under Windows NT/95/98/2000/XP. It is based on methods and algorithms coming from the area of Rough Sets. It comprises of two general components - the GUI front-end and the computational kernel. The kernel is based on renewed RSESlib library.
PC with 128+ MB RAM.
3 MB of disc space + space occupied by Java VM
Windows NT4/95/98/2000/XP/Vista/7 or Linux/i386
Java Runtime Environment (JRE) or Java SDK. We recommend the use of version 1.4.1 or higher.
The system, starting from version 2.0, is distributed as single self-installing bundle (for Windows). The installation procedure is described in User's Guide.
RSESlib is a library of functions for performing various data exploration tasks such as:
The library is implemented in Java and partially in C++. The development of library started in 1994 and the current version (2.0) is a renewed and significantly extended one. First version of library, after several extensions and updates was included in the computational kernel of mighty ROSETTA system.
The project approach provides easy manipulation of data entities represented as icons on the workplace. The operations are based on context menus attached to the visible objects and allowing execution of RSESlib procedures.
Basically, any data that is represented as the rectangular table of reasonable size. "Reasonable" size means that for the very large data tables the significant latency caused by the necessity of loading the data to/from memory/file may make some operations practically unmanageable. So, for the huge data one can not expect immediate results. However, the implementation of decomposition techniques as well as use of approximate techniques such as GA's (genetic algorithms) allow to cope with massive data sources.
speaking the limitations for data the RSES is able to process are only the
amount of RAM and HDD space you have.
From our experience:
It is not a general purpose Swiss-army-knife data analysis system. It was authors intention to produce simple yet capable system for Rough Set based computations. If you fancy advanced data manipulation, edition and visualisation tools, you better buy yourself MS-Excel, since RSES is definitely not this kind of toy. There are also not too many methods other than Rough Sets in RSES. We feel that if you want other methodology (statistics, neural nets etc.), you should turn to the specialised solutions, designed by experts.
Having in mind the plethora of different (both commercial and public domain ) tools for data MANIPULATION available on the market, we decided to focus on data EXPLORATION. Some manipulation procedures are still present in RSESlib, but if you just want to reformat your table, there are better ways.
RSES was designed and implemented as a result of research on Rough Set by:
Andrzej Skowron - Project Supervisor
GUI front-end design: Jan Bazan, Nguyen Hung Son, Andrzej Skowron and Marcin Szczuka.
GUI front-end implementation: Jan Bazan and Marcin Szczuka.
Kernel architecture design and implementation: Jan Bazan.
Computational algorithms implemented by (in alphabetical order): Jan Bazan, Rafał Latkowski, Nguyen Sinh Hoa, Nguyen Hung Son, Piotr Synak, Arkadiusz Wojna, Marcin Wojnarski and Jakub Wróblewski.
Copyright © 1994-2005 Logic Group, Institute of Mathematics, Warsaw University,