International Business Machines Corporation

Adrian Mahjour

Shaikh Shahriar Quader

Nitin Kumar Gupta

Pedro Miguel Barbas

Hima Patel

Petr Novotny

Berthold Reinwald

Aindrila Basak

Dheeraj Arremsetty

Carlo Appugliese

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.

Selecting a high coverage dataset

A cleansing operation defined for a data structure of a database managed by a database management system is obtained. The cleansing operation is performed on data of the data structure to obtain clean data. The cleansing operation that is defined for the data structure and performed on data of the data structure is performed by the database management system.

In-database data cleansing

A cleansing operation is performed on data of a data structure to obtain clean data. The clean data is stored as part of the data structure; however, the clean data is independent of the data. A mapping is performed to provide a set of ordered data that includes the data and the clean data.

In-database data cleansing and independent store of clean data

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Toronto, Canada

Adrian Mahjour