Titlebook: Rough Sets; International Joint JingTao Yao,Hamido Fujita,Fanzhang Li Conference proceedings 2022 The Editor(s) (if applicable) and The Au

HUSH

枯萎將要

Individual

GLADE

A Naive Bayes Classifier Based on?Neighborhood Granulationon of independence between features affects its classification accuracy. To solve this problem, this paper studies the theory of granular computing and proposes a naive Bayes classifier based on neighborhood granulation. The neighborhood discriminant function is introduced to perform single-feature

remission

Matrix Representations and?Interdependency on?an?,-fuzzy Covering-Based Rough Set matrix representations of lower and upper approximation operators is to make calculation more valid by means of operations on matrices. Furthermore, in accordance with the concept of .-base, we give a necessary and sufficient condition under what two .-fuzzy .-coverings can generate the same lower

Devastate

豪華

Rule Acquisition in?Generalized One-Sided Decision Systemsrmined by ordered attributes. In this paper, we propose methods of mining decision rules based on situations where only condition attributes are ordered (generalized one-sided formal decision context) and both the condition and decision attributes are ordered (generalized one-sided ordered formal de

INERT

Obloquy

Multi-label Feature Extraction With Distance-Based Graph Attention Networkta usually consider label correlations, while rarely consider sample correlations. In this paper, we propose a multi-label feature extraction with the distance-based graph attention network (DBGAT) algorithm. First, to easily extract the neighbors of the sample later, we construct an adjacency matri

圖表證明

Three-way Decision, Three-World Conception, and?Explainable AIr is to review and re-interpret various three-world conceptions through the lens of three-way decision. Three-world conceptions offer more insights into three-way decision with new viewpoints, methods, and modes. They can be used to construct easy-to-understand explanations in explainable artificial intelligence (XAI).