ECS -- an Interactive Tool for Data Quality Assurance

Based on this a wide variate The development of machine learning (ML) based systems of data quality properties is addressed. Be it the identification has led to a widespread use in research, industry as well as of single data points like outliers, false annotations in the everyday life. Even though ML systems show great or isolated data or the identification of groups of data performance in solving complex tasks, their use is mostly points like decision boundaries and local data point groups limited to domains, where wrong decisions only have minor of identical output. The ECS makes it possible to identify all consequences. The application of ML systems in high-risk data points which do not match specifiable conditions. The domains currently is problematic due to the needed quality, method itself is thereby created in such a way that interactions lack of trustworthiness and the expected legal basis. To give between the user and the data are supported in order to a legal framework for the application of ML systems the European simplify and speed up the quality assurance process. AI act (European Comission 2021) is at the moment under development.