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
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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。
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.
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