ROSE2

ROSE2 (Rough Sets Data Explorer) is a software implementing basic elements of the rough set theory and rule discovery techniques. It has been created at the Laboratory of Intelligent Decision Support Systems of the Institute of Computing Science in Poznan, basing on fourteen-year experience in rough set based knowledge discovery and decision analysis.

All computations are based on rough set fundamentals introduced by Z. Pawlak. One of implemented extensions applies the variable precision rough set model defined by W. Ziarko. It is particularly useful in analysis of data sets with large boundary regions. Another extension implements the rough set approach based on a similarity relation, as proposed by R. Slowinski. The similarity relation is assessed from data via inductive learning.

The ROSE2 system is a succesor of RoughDAS and RoughClass systems. RoughDAS is historically one of the first successful implementations of the rough set theory, which has been used in many real life applications.

The system contains several tools for rough set based knowledge discovery, e.g.:

• data preprocessing, including discretization of numerical attributes,
• performing a standard and an extended rough set based analysis of data,
• search of a core and reducts of attributes permitting data reduction,
• inducing sets of decision rules from rough approximations of decision classes,
• evaluating sets of rules in classifiaction experiments,
• using sets of decision rules as classifiers.

Features

ROSE2 is an interactive system running on 32-bit Microsoft Windows operating systems (Windows 95 and better). Core modules were written in C++ (ANSI standard), while the interface modules were developed using Borland C++ Builder and Borland Delphi.

The system consists of a graphical environment and a set of separate computational modules. The modules are platform-independent and can be recompiled for different operating systems, including Linux. The environment acts as an overlay on all computational modules. So it is quite easy to add new modules to the system and that is an important characteristic. This guarantees greater expandability of the system in the future.

ROSE2 is designed to be easy in use, point and click, menu-driven, user friendly tool for exploration and data analysis. It is meant as well for experts as for occasional users who want to do the data analysis. System communicates with users using dialog windows and all the results are represented in the environment. Data can be edited using a spreadsheet-like interface.

Data editor

 

Features currently offered by computational modules include:

• data validation and preprocessing,
• automatic discretization of continuously-valued attributes (using local and global techniques) as well as user-driven discretization,
• qualitative estimation of the ability of the condition attributes to approximate the objects' classification, using either standard rough set model or variable precision model,
• rough set data analysis based on similarity relation,
• finding the core of attributes as well as looking for reducts in the information table (either all reducts or a population of reducts of predetermined size) using several methods such,
• examining the relative significance of a given attribute for the classification of objects, by observing the changes in the quality of classification,
• reducing superfluous attributes and selecting the most significant attributes for the classification of objects; there are available several techniques that support the choice o subsets of attributes ensuring a satisfactory quality of the classification (e.g. the technique of adding the most discriminatory attributes to the core),
• inducing decision rules using either LEM2 or MODLEM, or EXPLORE algorithms,
• applying a set of decision rules to classify new objects using a distance-based classifier,
• evaluation of the sets of decision rules using leaving-one-out and k-fold cross validation techniques.

Download

Free version of ROSE2 is available for downloading. It can be used for any non-profit activities. Please read the detailed license agreement on the download page.

References

If you use ROSE2 as a computational tool in any published work, we kindly ask you for mentioning it. You could quote the following references:

• B.Predki, R.Slowinski, J.Stefanowski, R.Susmaga, Sz.Wilk: ROSE - Software Implementation of the Rough Set Theory. In: L.Polkowski, A.Skowron, eds. Rough Sets and Current Trends in Computing, Lecture Notes in Artificial Intelligence, vol. 1424. Springer-Verlag, Berlin (1998), 605-608.
• B.Predki, Sz.Wilk: Rough Set Based Data Exploration Using ROSE System. In: Z.W.Ras, A.Skowron, eds. Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence, vol. 1609. Springer-Verlag, Berlin (1999), 172-180.

Please send us an exact reference of your publication. We are very interested in hearing about effects of your application of ROSE2.

Contact

All remarks, suggestions, questions and bug reports are welcome. Please, do not hesitate to contact the following persons:

Szymon Wilk
Bartłomiej Prędki
Jerzy Stefanowski