APPROXIMATE METRIC FOR DATASET USING REPRESENTATIVE SUBSET

Abstract: techniques for processing a large dataset to extract information from the dataset, where the processing is performed by multiple systems and where the entire dataset, due to its size, cannot be loaded into the memory of any one of the multiple systems. in certain implementations, the information extracted from the dataset is in the form of a set of one or more statistical metrics computed for the dataset. for example, the dataset may include datapoints related to a machine-learning (ml) model, and a metric value can be computed for the ml model based upon the dataset datapoints. the metric value may, for example, be a metric that measures the performance of the ml model.

Inventor(s): Furqan Abdul Samad Shaikh, Amit Kumar Prajapati, Antariksha Bhaduri

CPC Classification: G06F16/278 ({Data partitioning, e.g. horizontal or vertical partitioning})

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