Loading patent…
AssigneeSoftware AG
InventorsMohamed Abdelaal, Samuel Lokadjaja, Arne Kreuz
Estimating the term…
Certain example embodiments relate to dashboards that help streamline and automate data quality management processes used with machine learning (ML) models and ML-enabled technology. A clean dataset is initialized from a dirty dataset. A search space is the set of all possible combinations of available error detection algorithms and data repair algorithms. A scoring function measures performance of a given error detection algorithm and data repair algorithm combination on the clean dataset. An ML model is trained using the clean dataset. Best error detection and data repair algorithms are selected, based on an optimization on the set of all possible combinations, and the defined scoring function. The selected best error detection algorithm is applied to the clean dataset, and a repaired dataset is generated using the selected best repair algorithm. The clean dataset is set to the repaired dataset. This procedure is repeated until a condition is met.
A machine learning (ML) model dataset preparation method for use with a system having access to a plurality of error detection algorithms, a plurality of data repair algorithms, and an ML model, the method comprising:
A non-transitory computer readable storage medium storing instructions that, when executed, cause a processor of a system having access to a plurality of error detection algorithms, a plurality of data repair algorithms, and an ML model, to perform operations comprising:
A machine learning (ML) model dataset preparation system having access to a plurality of error detection algorithms, a plurality of data repair algorithms, and an ML model, the system comprising:
Dependencies are inferred from the claim text.