通用数据集的GouDa生成:改进数据准备管道的分析和评估

Valerie Restat, Gerrit Boerner, Andrew P. Conrad, U. Störl
{"title":"通用数据集的GouDa生成:改进数据准备管道的分析和评估","authors":"Valerie Restat, Gerrit Boerner, Andrew P. Conrad, U. Störl","doi":"10.1145/3533028.3533311","DOIUrl":null,"url":null,"abstract":"Data preparation is necessary to ensure data quality in machine learning-based decisions and data-driven systems. A variety of different tools exist to simplify this process. However, there is often a lack of suitable data sets to evaluate and compare existing tools and new research approaches. For this reason, we implemented GouDa, a tool for generating universal data sets. GouDa can be used to create data sets with arbitrary error types at arbitrary error rates. In addition to the data sets with automatically generated errors, ground truth is provided. Thus, GouDa can be used for the extensive analysis and evaluation of data preparation pipelines.","PeriodicalId":345888,"journal":{"name":"Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GouDa - generation of universal data sets: improving analysis and evaluation of data preparation pipelines\",\"authors\":\"Valerie Restat, Gerrit Boerner, Andrew P. Conrad, U. Störl\",\"doi\":\"10.1145/3533028.3533311\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data preparation is necessary to ensure data quality in machine learning-based decisions and data-driven systems. A variety of different tools exist to simplify this process. However, there is often a lack of suitable data sets to evaluate and compare existing tools and new research approaches. For this reason, we implemented GouDa, a tool for generating universal data sets. GouDa can be used to create data sets with arbitrary error types at arbitrary error rates. In addition to the data sets with automatically generated errors, ground truth is provided. Thus, GouDa can be used for the extensive analysis and evaluation of data preparation pipelines.\",\"PeriodicalId\":345888,\"journal\":{\"name\":\"Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3533028.3533311\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3533028.3533311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在基于机器学习的决策和数据驱动系统中,数据准备是确保数据质量的必要条件。有许多不同的工具可以简化这个过程。然而,往往缺乏适当的数据集来评估和比较现有的工具和新的研究方法。出于这个原因,我们实现了GouDa,一个生成通用数据集的工具。GouDa可以用来创建具有任意错误类型和任意错误率的数据集。除了自动生成错误的数据集外,还提供了地面真实值。因此,GouDa可以用于数据准备管道的广泛分析和评估。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
GouDa - generation of universal data sets: improving analysis and evaluation of data preparation pipelines
Data preparation is necessary to ensure data quality in machine learning-based decisions and data-driven systems. A variety of different tools exist to simplify this process. However, there is often a lack of suitable data sets to evaluate and compare existing tools and new research approaches. For this reason, we implemented GouDa, a tool for generating universal data sets. GouDa can be used to create data sets with arbitrary error types at arbitrary error rates. In addition to the data sets with automatically generated errors, ground truth is provided. Thus, GouDa can be used for the extensive analysis and evaluation of data preparation pipelines.
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
自引率
0.00%
发文量
0
期刊最新文献
dcbench GouDa - generation of universal data sets: improving analysis and evaluation of data preparation pipelines How I stopped worrying about training data bugs and started complaining Evaluating model serving strategies over streaming data Accelerating container-based deep learning hyperparameter optimization workloads
×
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