Attribute reduction methods in fuzzy rough set theory: An overview, comparative experiments, and new directions

Z Yuan, H Chen, P **e, P Zhang, J Liu, T Li - Applied Soft Computing, 2021‏ - Elsevier
Fuzzy rough set theory is a powerful tool to deal with uncertainty information, which has
been successfully applied to the fields of attribute reduction, rule extraction, classification …

Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches

R Jensen, Q Shen - IEEE Transactions on knowledge and data …, 2004‏ - ieeexplore.ieee.org
Semantics-preserving dimensionality reduction refers to the problem of selecting those input
features that are most predictive of a given outcome; a problem encountered in many areas …

GBNRS: A novel rough set algorithm for fast adaptive attribute reduction in classification

S **a, H Zhang, W Li, G Wang, E Giem… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Feature reduction is an important aspect of Big Data analytics on today's ever-larger
datasets. Rough sets are a classical method widely applied in attribute reduction. Most …

Mining smart card data for transit riders' travel patterns

X Ma, YJ Wu, Y Wang, F Chen, J Liu - Transportation Research Part C …, 2013‏ - Elsevier
To mitigate the congestion caused by the ever increasing number of privately owned
automobiles, public transit is highly promoted by transportation agencies worldwide. A better …

[کتاب][B] Data mining: concepts and techniques

J Han, J Pei, H Tong - 2022‏ - books.google.com
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

Three-way decision making approach to conflict analysis and resolution using probabilistic rough set over two universes

B Sun, X Chen, L Zhang, W Ma - Information Sciences, 2020‏ - Elsevier
Conflict analysis aims to identify the intrinsic reasons and find a feasible consensus strategy
for a conflict situation. Rough set theory was used to study conflict analysis decision-making …

Rudiments of rough sets

Z Pawlak, A Skowron - Information sciences, 2007‏ - Elsevier
Worldwide, there has been a rapid growth in interest in rough set theory and its applications
in recent years. Evidence of this can be found in the increasing number of high-quality …

A sensitivity analysis in MCDM problems: A statistical approach

I Mukhametzyanov, D Pamucar - Decision making: applications …, 2018‏ - dmame-journal.org
This study provides a model for result consistency evaluation of multi-criteria decision-
making (MDM) methods and selection of the optimal one. The study presents the results of …

Rough sets theory for multicriteria decision analysis

S Greco, B Matarazzo, R Slowinski - European journal of operational …, 2001‏ - Elsevier
The original rough set approach proved to be very useful in dealing with inconsistency
problems following from information granulation. It operates on a data table composed of a …

Rough set theory and its applications to data analysis

Z Pawlak - Cybernetics & Systems, 1998‏ - Taylor & Francis
This paper gives basic ideas of rough set theory a new approach to data analysis. The lower
and upper approximation of a set, the basic operations of the theory, are intuitively explained …