Search
Search Results
-
Neighborhood rough set with neighborhood equivalence relation for feature selection
Feature selection of the neighborhood rough set is an important step in preprocessing the data and improving classification performance. Neighborhood...
-
A multigranulation rough set model based on variable precision neighborhood and its applications
As combinations of neighborhood rough sets and multigranulation rough sets (MRSs), optimistic and pessimistic neighborhood MRSs can handle complex...
-
ASFS: A novel streaming feature selection for multi-label data based on neighborhood rough set
Neighborhood rough set based online streaming feature selection methods have aroused wide concern in recent years and played a vital role in...
-
Dynamic updating approximations of local generalized multigranulation neighborhood rough set
The approximation space in rough set theory is important for dealing with uncertainties. As the information contained in various information systems...
-
WalkNAR: A neighborhood rough sets-based attribute reduction approach using random walk
Neighborhood rough sets, as an effective tool for processing numerical data, is widely used in many fields, such as data mining, machine learning and...
-
Online multi-label stream feature selection based on neighborhood rough set with missing labels
Multi-label feature selection has been essential in many big data applications and plays a significant role in processing high-dimensional data....
-
Approximate Supplement-Based Neighborhood Rough Set Model in Incomplete Hybrid Information Systems
Incomplete hybrid information systems (IHISs) contain hybrid data (e.g., categorical data, numerical data) and incomplete data. With the development...
-
An improved ID3 algorithm based on variable precision neighborhood rough sets
The classical ID3 decision tree algorithm cannot directly handle continuous data and has a poor classification effect. Moreover, most of the existing...
-
Maximum relevance minimum redundancy-based feature selection using rough mutual information in adaptive neighborhood rough sets
Feature selection based on neighborhood rough sets (NRSs) has become a popular area of research in data mining. However, the limitation that NRSs...
-
Feature selection based on multi-perspective entropy of mixing uncertainty measure in variable-granularity rough set
Neighborhood rough set is an important model in feature selection. However, it only determines the granularity of the neighborhood from a feature...
-
An efficient approach to attribute reductions of quantitative dominance-based neighborhood rough sets based on graded information granules
Lower approximations of quantitative dominance-based neighborhood rough sets aim to enhance the consistency of dominance principles by filtering out...
-
Hypersphere Neighborhood Rough Set for Rapid Attribute Reduction
Neighborhood rough set (NRS) has been successfully applied to attribute reduction for numeric data. Most existing algorithms have a time complexity...
-
Tri-level attribute reduction based on neighborhood rough sets
Tri-level attribute reduction is an interesting topic that aims to reduce the data dimensionality from different levels and granularity perspectives....
-
Feature selection using relative dependency complement mutual information in fitting fuzzy rough set model
As a reliable and valid tool for analyzing uncertain information, fuzzy rough set theory has attracted widespread concern in feature selection....
-
Quasi-atomic relations based rough set model and convex geometry
Numerous studies have extensively examined the correlation between convex structures and covering rough set models. However, limited attention has...
-
A novel approach based on rough set theory for analyzing information disorder
The paper presents and evaluates an approach based on Rough Set Theory, and some variants and extensions of this theory, to analyze phenomena related...
-
Accelerated multi-granularity reduction based on neighborhood rough sets
The notion of multi-granularity has been introduced into various mathematical models in granular computing. For example, neighborhood rough sets can...
-
Neighborhood Rough Neural Network Approach for COVID-19 Image Classification
The rapid spread of the new Coronavirus, COVID-19, causes serious symptoms in humans and can lead to fatality. A COVID-19 infected person can...
-
Decision Theoretic Rough Set-Based Neighborhood for Self-Organizing Map
A decision theoretic rough set-based neighborhood selection process is developed for self-organizing maps. While the neighborhood of the winner...
-
Neighborhood based decision theoretic rough set under dynamic granulation for BCI motor imagery classification
Brain Computer Interface is an interesting and important research field that has contributed widespread application systems. In the medical field, it...
