Rough sets

1995/11/01 by Zdzislaw Pawlak, Zdzisław Pawlak, Jerzy Grzymala-Busse +4 · 11 citations
Computer Science · #Rough Sets and Fuzzy Logic #Data Management and Algorithms

paper · pdf · doi:10.1145/219717.219791

Abstract

Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.

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• An Empirical Analysis of Rough Set Categorical Clustering Techniques. [europepmc]
• Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications. [europepmc]
• A progressive approach to multi-criteria group decision-making: N-bipolar hypersoft topology perspective. [europepmc]
• Unsupervised attribute reduction based on variable precision weighted neighborhood dependency. [europepmc]

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