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Local neighborhood rough set

Knowledge-Based Systems, 2018
Abstract With the advent of the age of big data, a typical big data set called limited labeled big data appears. It includes a small amount of labeled data and a large amount of unlabeled data. Some existing neighborhood-based rough set algorithms work well in analyzing the rough data with numerical features.
Qi Wang   +4 more
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Pseudo-label neighborhood rough set: Measures and attribute reductions

International Journal of Approximate Reasoning, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xibei Yang   +4 more
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Neighborhood rough set based heterogeneous feature subset selection

Information Sciences, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Qinghua   +3 more
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GBRS: A Unified Granular-Ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set

IEEE Transactions on Neural Networks and Learning Systems
Pawlak rough set (PRS) and neighborhood rough set (NRS) are the two most common rough set theoretical models. Although the PRS can use equivalence classes to represent knowledge, it is unable to process continuous data. On the other hand, NRSs, which can process continuous data, rather lose the ability of using equivalence classes to represent ...
Shuyin Xia   +7 more
openaire   +4 more sources

Subset neighborhood rough sets

Knowledge-Based Systems, 2022
We present a novel kind of neighborhood, named subset neighborhood and denoted as Sρ-neighborhood. It is defined under an arbitrary binary relation using the inclusion relations between Nρ-neighborhoods. We study its relationships with some kinds of neighborhood systems given in the literature.
Tareq M. Al-shami, Davide Ciucci
openaire   +1 more source

Neighborhood Systems: Rough Set Approximations and Definability

Fundamenta Informaticae, 2018
The notions of approximation and definability in classical rough set theory and their generalizations have received much attention. In this paper, we study such generalizations from the perspective of neighborhood systems. We introduce four different types of definability, called interior definability, closure definability, interior-closure (IC ...
Syau, Yu-Ru   +2 more
openaire   +2 more sources

Neighborhood Systems and Variable Precision Generalized Rough Sets

Fundamenta Informaticae, 2017
In this paper, we present the connection between the concepts of Variable Precision Generalized Rough Set model (VPGRS-model) and Neighborhood Systems through binary relations. We provide characterizations of lower and upper approximations for VPGRS-model by introducing minimal neighborhood systems.
Syau, Yu-Ru   +2 more
openaire   +2 more sources

Knowledge Granulation Based Roughness Measure for Neighborhood Rough Sets

2013 Third International Conference on Intelligent System Design and Engineering Applications, 2013
Neighborhood rough sets have been applied to feature selection and attribute reduction successfully. Roughness is an important uncertainty measure for a concept in an information system. In this paper, generalized from the classical roughness, a new uncertainty measure based on granulation of knowledge for neighborhood rough sets is proposed to ...
Chengdong Yang   +2 more
openaire   +1 more source

Neighborhood Rough Set Approach With Biometric Application

International Journal of Sociotechnology and Knowledge Development, 2022
This paper provides a new approach for human identification based on Neighborhood Rough Set (NRS) algorithm with biometric application of ear recognition. The traditional rough set model can just be used to evaluate categorical features. The neighborhood model is used to evaluate both numerical and categorical features by assigning different thresholds
B. Lavanya   +2 more
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A soft neighborhood rough set model and its applications

Information Sciences, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
An, Shuang   +4 more
openaire   +1 more source

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