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":"81 1","pages":"0"},"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\":\"81 1\",\"pages\":\"0\"},\"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}
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.