Using specified performance attributes to configure machine learning pipeline stages for an ETL job

Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning p...

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Bibliographische Detailangaben
Hauptverfasser:	Saussy, Juliana, Jones, Timothy, Qureshi, Shehzad, Ash, Stephen Michael, Borthwick, Andrew, Damle, Prajakta Datta, Heinermann, Adam Lawrence Joseph, Gupta, Anurag Windlass, Kommaranahalli Rudramuni, Chethan, Desai, Alaykumar Navinchandra, Shah, Mehul A, Maynard-Zhang, Pedrito Uriah, Shah, Mehul Y, Sharma, Abhishek, Dobroshinsky, Sergei
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
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Beschreibung
Zusammenfassung:	Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning pipeline. The configured stage may then be used when training the model. The trained machine learning pipeline may then be applied as part of a transformation operation included in an ETL job performed by the ETL system.