CEKA: a tool for mining the wisdom of crowds

J. Zhang, V. Sheng, B. Nicholson, Xindong Wu
{"title":"CEKA: a tool for mining the wisdom of crowds","authors":"J. Zhang, V. Sheng, B. Nicholson, Xindong Wu","doi":"10.5555/2789272.2912090","DOIUrl":null,"url":null,"abstract":"CEKA is a software package for developers and researchers to mine the wisdom of crowds. It makes the entire knowledge discovery procedure much easier, including analyzing qualities of workers, simulating labeling behaviors, inferring true class labels of instances, filtering and correcting mislabeled instances (noise), building learning models and evaluating them. It integrates a set of state-of-the-art inference algorithms, a set of general noise handling algorithms, and abundant functions for model training and evaluation. CEKA is written in Java with core classes being compatible with the well-known machine learning tool WEKA, which makes the utilization of the functions in WEKA much easier.","PeriodicalId":14794,"journal":{"name":"J. Mach. Learn. Res.","volume":"10 1","pages":"2853-2858"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Mach. Learn. Res.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/2789272.2912090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

Abstract

CEKA is a software package for developers and researchers to mine the wisdom of crowds. It makes the entire knowledge discovery procedure much easier, including analyzing qualities of workers, simulating labeling behaviors, inferring true class labels of instances, filtering and correcting mislabeled instances (noise), building learning models and evaluating them. It integrates a set of state-of-the-art inference algorithms, a set of general noise handling algorithms, and abundant functions for model training and evaluation. CEKA is written in Java with core classes being compatible with the well-known machine learning tool WEKA, which makes the utilization of the functions in WEKA much easier.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CEKA:挖掘群体智慧的工具
CEKA是开发人员和研究人员挖掘群体智慧的软件包。它使整个知识发现过程变得更加容易,包括分析工作者的素质,模拟标记行为,推断实例的真实类标签,过滤和纠正错误标记的实例(噪声),建立学习模型并对其进行评估。它集成了一套最先进的推理算法,一套通用的噪声处理算法,以及丰富的模型训练和评估功能。CEKA是用Java编写的,其核心类与著名的机器学习工具WEKA兼容,这使得使用WEKA中的函数更加容易。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Scalable Computation of Causal Bounds A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning Adaptive False Discovery Rate Control with Privacy Guarantee Fairlearn: Assessing and Improving Fairness of AI Systems Generalization Bounds for Adversarial Contrastive Learning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1