SELECTING A HIGH COVERAGE DATASET

SELECTING A HIGH COVERAGE DATASET

Providing a representative dataset from an initial dataset by accessing a dataset associated with a machine learning model, receiving input parameters associated with the representative dataset selection, the input parameters including an evaluation metric, determining a density of a plurality of da...

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Hauptverfasser: APPUGLIESE, CARLO, Basak, Aindrila, Reinwald, Berthold, Arremsetty, Dheeraj, Mahjour, Adrian, Quader, Shaikh Shahriar, Novotny, Petr
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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creator APPUGLIESE, CARLO
Basak, Aindrila
Reinwald, Berthold
Arremsetty, Dheeraj
Mahjour, Adrian
Quader, Shaikh Shahriar
Novotny, Petr
description Providing a representative dataset from an initial dataset by accessing a dataset associated with a machine learning model, receiving input parameters associated with the representative dataset selection, the input parameters including an evaluation metric, determining a density of a plurality of datapoints associated with the dataset, training a first iteration of a machine learning model using a first data point selected according to the density, determining a first value of the evaluation metric for the first iteration of the machine learning model, generating a representative subset based on the first value of the evaluation metric value, and providing the representative dataset and a final machine learning model trained using the representative dataset.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title SELECTING A HIGH COVERAGE DATASET
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