METADATA-DRIVEN FEATURE STORE FOR MACHINE LEARNING SYSTEMS

METADATA-DRIVEN FEATURE STORE FOR MACHINE LEARNING SYSTEMS

A method includes identifying one or more transformations to be applied in order to generate one or more features or feature sets. The method also includes generating metadata identifying the one or more features or feature sets and the one or more transformations. The method further includes using...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Tchankotadze, David, Fischer, Jeffrey M, Viswanathan, Siddharth, Yadav, Rahul, Sureka, Rohit P
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung:A method includes identifying one or more transformations to be applied in order to generate one or more features or feature sets. The method also includes generating metadata identifying the one or more features or feature sets and the one or more transformations. The method further includes using the metadata to determine the one or more features or feature sets for specified data and storing the one or more determined features or feature sets in a feature store. In addition, the method includes outputting at least some of the one or more determined features or feature sets or data associated with the at least some of the one or more determined features or feature sets from the feature store to at least one machine learning model.