Feature selection is a significant preprocessing technique for data mining, which can
promote the accuracy of data classification and shrink feature space by eliminating …

Pythagorean fuzzy set theory is one of the significant tools to deal with real-life problems
which are prone to imprecision, partial truth or uncertainty. A Pythagorean fuzzy set reports …

In the field of rough set, how to improve the efficiency of obtaining reduct has been paid
much attention to. One of the typical strategies is to reduce the number of comparisons …

In this study, a granular ball based selector was developed for reducing the dimensions of
data from the perspective of attribute reduction. The granular ball theory offers a data …

In neighborhood rough set, radius is a key factor. Different radii may generate different
neighborhood relations for discriminating samples. Unfortunately, it is possible that two …

As one of the crucial topics in the development of rough set, attribute reduction has received
extensive attentions because it is practical and interpretable for us to perform dimensional …

Neighborhood-based attribute reduction plays a vital role in pattern recognition, for selecting
a series of informative and relevant attributes from data sets. The increase in dimensionality …

As a prominent model of granular computing, neighborhood rough set provides clear
granularity organization and expression in terms of inherent parameter (neighborhood …

In rough set based Granular Computing, neighborhood relation has been widely accepted
as one of the most popular approaches for realizing information granulation. Such approach …

In the field of Granular Computing (GrC), feature selection is an attractive task. Some basics
of GrC such as information granulation and granularity have well guided the explorations of …