粒度计算范式在知识归纳中的应用

Q3 Engineering

Journal of Information and Communication Convergence Engineering Pub Date : 2017-08-04 DOI:10.5281/ZENODO.1132435

I. Sikder

{"title":"粒度计算范式在知识归纳中的应用","authors":"I. Sikder","doi":"10.5281/ZENODO.1132435","DOIUrl":null,"url":null,"abstract":"This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms. Keywords—Concept approximation, granular computing, reducts, rough set theory, rule induction.","PeriodicalId":37530,"journal":{"name":"Journal of Information and Communication Convergence Engineering","volume":"11 1","pages":"1140-1143"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Application of Granular Computing Paradigm in Knowledge Induction\",\"authors\":\"I. Sikder\",\"doi\":\"10.5281/ZENODO.1132435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms. Keywords—Concept approximation, granular computing, reducts, rough set theory, rule induction.\",\"PeriodicalId\":37530,\"journal\":{\"name\":\"Journal of Information and Communication Convergence Engineering\",\"volume\":\"11 1\",\"pages\":\"1140-1143\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information and Communication Convergence Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.1132435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Communication Convergence Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.1132435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 3

摘要

本文阐述了粒度计算方法，即粗糙集理论在数据挖掘中的应用。本文概述了粒度计算的形式，并阐述了粗糙集理论的数学基础，该理论已被数据挖掘和机器学习界广泛使用。举例说明了实际应用，并将其分类性能与其他竞争对手的机器学习算法进行了比较。粗糙集规则归纳模型的预测性能显示出与其他竞争算法相比的相对成功。关键词——概念近似，粒度计算，约简，粗糙集理论，规则归纳。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Application of Granular Computing Paradigm in Knowledge Induction

This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms. Keywords—Concept approximation, granular computing, reducts, rough set theory, rule induction.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Information and Communication Convergence Engineering Engineering-Media Technology

CiteScore

1.10

自引率

0.00%

发文量

期刊介绍： Journal of Information and Communication Convergence Engineering (J. Inf. Commun. Converg. Eng., JICCE) is an official English journal of the Korea Institute of Information and Communication Engineering (KIICE). It is an international, peer reviewed, and open access journal that is published quarterly in March, June, September, and December. Its objective is to provide rapid publications of original and significant contributions and it covers all areas related to information and communication convergence engineering including the following areas: communication system and applications, networking and services, intelligent information system, multimedia and digital convergence, semiconductors and communication devices, imaging and biomedical engineering, and computer vision and autonomous vehicles.