SELF-IMPROVING BAYESIAN NETWORK LEARNING

SELF-IMPROVING BAYESIAN NETWORK LEARNING

A method, a computer system, and a computer program product for creating multiple models asynchronously is provided. Embodiments of the present invention may include receiving input data, wherein input data includes a full training dataset. Embodiments of the present invention may include building,...

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Hauptverfasser: Pascale, Alessandra, Ganguly, Debasis, Tommasi, Pierpaolo, Deparis, Stephane
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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creator Pascale, Alessandra
Ganguly, Debasis
Tommasi, Pierpaolo
Deparis, Stephane
description A method, a computer system, and a computer program product for creating multiple models asynchronously is provided. Embodiments of the present invention may include receiving input data, wherein input data includes a full training dataset. Embodiments of the present invention may include building, asynchronously, one or more Bayesian network models using one or more portions of the input data on a first pipeline and building a free learning model using the full training dataset on a second pipeline. Embodiments of the present invention may include retrieving the one or more Bayesian network models from the first pipeline. Embodiments of the present invention may include retrieving the free learning model from the second pipeline.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title SELF-IMPROVING BAYESIAN NETWORK LEARNING
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