Journal ArticleDOI
Robust supervised rough granular description model with the principle of justifiable granularity
Reads0
Chats0
TLDR
Experimental results demonstrate that the proposed Dempster–Shafer theory-based rough granular description model is reasonable, effective, and robust, and is a promising rough granularity description model for complex data in real-world applications.About:
This article is published in Applied Soft Computing.The article was published on 2021-10-01. It has received 28 citations till now. The article focuses on the topics: Rough set & Granular computing.read more
Citations
More filters
Journal ArticleDOI
Dynamic updating approximations of local generalized multigranulation neighborhood rough set
Weihua Xu,Kehua Yuan,Wentao Li +2 more
TL;DR: A dynamic approximation update mechanism of multigranulation data from local viewpoint is investigated and the corresponding dynamic update algorithms for dynamic objects are proposed based on local generalized multIGranulation rough set model.
Journal ArticleDOI
Dynamic updating approximations of local generalized multigranulation neighborhood rough set
Weihua Xu,Kehua Yuan,Wentao Li +2 more
Journal ArticleDOI
Granular ball guided selector for attribute reduction
TL;DR: The granular ball theory offers a data-adaptive strategy for realizing information granulation process and thereafter, the procedure of deriving the reduct can be redesigned from a novel perspective.
Journal ArticleDOI
Temporal-spatial three-way granular computing for dynamic text sentiment classification
TL;DR: This article proposed a temporal-spatial three-way multi-granularity learning framework for dynamic text sentiment classification to continually address dynamic data uncertainty in the boundary region according to the monotonous variation of coarser-to-finer granularity.
Journal ArticleDOI
Random sampling accelerator for attribute reduction
TL;DR: In this paper, an accelerator based on random sampling is developed to reduce the time consumption of deriving reducts and then the average speedup ratio can exceed 10, and the reduct derived by the accelerator can offer competent performance in classification task.
References
More filters
Journal ArticleDOI
Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic
TL;DR: M Modes of information granulation (IG) in which the granules are crisp (c-granular) play important roles in a wide variety of methods, approaches and techniques, but this does not reflect the fact that in almost all of human reasoning and concept formation thegranules are fuzzy (f- Granular).
Journal ArticleDOI
Variable precision rough set model
TL;DR: A generalized model of rough sets called variable precision model (VP-model), aimed at modelling classification problems involving uncertain or imprecise information, is presented and the main concepts are introduced formally and illustrated with simple examples.
Book ChapterDOI
A k-nearest neighbor classification rule based on Dempster-Shafer theory
TL;DR: In this paper, the problem of classifying an unseen pattern on the basis of its nearest neighbors in a recorded data set is addressed from the point of view of Dempster-Shafer theory to provide a global treatment of such issues as ambiguity and distance rejection, and imperfect knowledge regarding the class membership of training patterns.
A k -Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory.
TL;DR: In this paper, the problem of classifying an unseen pattern on the basis of its nearest neighbors in a recorded data set is addressed from the point of view of Dempster-Shafer theory to provide a global treatment of such issues as ambiguity and distance rejection, and imperfect knowledge regarding the class membership of training patterns.
Journal ArticleDOI
Neighborhood rough set based heterogeneous feature subset selection
TL;DR: A neighborhood rough set model is introduced to deal with the problem of heterogeneous feature subset selection and Experimental results show that the neighborhood model based method is more flexible to deals with heterogeneous data.
Related Papers (5)
Rough sets and intelligent systems paradigms : International Conference, RSEISP 2007 Warsaw, Poland, June 28-30, 2007 : proceedings
Rseisp,Marzena Kryszkiewicz +1 more