This paper presents a review of the current literature on rough-set-and near-set-based
approaches to solving various problems in medical imaging such as medical image …

Feature selection plays an important role in pattern recognition and machine learning.
Feature evaluation and classification complexity estimation arise as key issues in the …

This paper proposes a reduct construction method based on discernibility matrix
simplification. The method works in a similar way to the classical Gaussian elimination …

The fuzzy rough set (FRS) model has been introduced to handle databases with real values.
However, FRS was sensitive to misclassification and perturbation (here misclassification …

One of the strengths of rough set theory is the fact that an unknown target concept can be
approximately characterized by existing knowledge structures in a knowledge base …

A relative reduct can be considered as a minimum set of attributes that preserves a certain
classification property. This paper investigates three different classification properties, and …

This paper presents a general framework for the study of relation-based (I, T)-intuitionistic
fuzzy rough sets by using constructive and axiomatic approaches. In the constructive …

The fuzzy-rough set (FRS) methodology, as a useful tool to handle discernibility and
fuzziness, has been widely studied. Some researchers studied on the rough approximation …

Based on an intuitionistic knowledge content nature of information gain, the concept of
combination entropy CE (A) in incomplete information systems is first introduced, and some …

A recent TRANSACTIONS ON FUZZY SYSTEMS paper proposing a new fuzzy-rough
feature selector (FRFS) has claimed that the more attributes remain in datasets, the better …