The aim of attribute reduction is to remove redundant attributes as well as find important ones for classification. Several types of attribute reduction have ...
This work provides an introduction to a rough set approach to attribute reduction, which deals with uncertainty decision classes with respect to attributes ...
The aim of attribute reduction is to remove redundant attributes as well as find important ones for classification. Several types of attribute reduction have ...
A few computational approaches to the proposed reducts are briefly described. I. INTRODUCTION. The usefulness andapplicability of rough sets proposed by. Pawlak ...
Structure-Based Attribute Reduction: A Rough Set Approach · List of references · Publications that cite this publication.
May 15, 2024 · The current goal of rough set attribute reduction focuses more on minimizing the number of reduced attributes, but ignores the spatial ...
Oct 22, 2024 · In this paper, structure-enhancing approaches to attribute reduction are proposed. Ten kinds of meaningful reducts are defined.
Dec 8, 2010 · I tried RSAR, a free package, but I wonder if there any other good attribute reducers out there. Even packages for R or MATLAB, any resource ...
Among them, the attribute reduction algorithms based on rough set theory not only achieve optimal or suboptimal reduction results but also have good ...
This work presented the innovative application of three metaheuristics for attribute reduction based on the Rough Set theory (RST).