Annotation of a Machine Learning Pipeline with Operational Semantics

A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning (ML) pipeline, is implemented over a data flow graph (DFG) with nodes configured to support rich semantics. The rich semantics include two or more operational s...

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Hauptverfasser:	GANTI, RAGHU KIRAN, Rosenkranz, Joshua M, HOANG TRONG, Tuan Minh, SRIVATSA, MUDHAKAR, Andrade Costa, Carlos Henrique, Chu, Linsong
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
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creator	GANTI, RAGHU KIRAN Rosenkranz, Joshua M HOANG TRONG, Tuan Minh SRIVATSA, MUDHAKAR Andrade Costa, Carlos Henrique Chu, Linsong
description	A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning (ML) pipeline, is implemented over a data flow graph (DFG) with nodes configured to support rich semantics. The rich semantics include two or more operational semantics, and at least one lineage semantic to selectively combine features that trace lineage to a common input object. The lineage semantic is leveraged to associate training and testing data set pairs in cross validation of the trained ML models produced from parallelizing the selection of ML pipelines.
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subjects	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
title	Annotation of a Machine Learning Pipeline with Operational Semantics
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