Importance

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Abstract

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for training a machine learning model comprising a hidden module and an output module and configured for identifying one of a plurality of original labels for an input. In accordance with one embodiment, a method is provided that includes generating sufficiently-labeled data comprising example-pairs each associated with a sufficient label. The sufficient label of an example-pair indicates whether a first and a second input example have the same original label. The method further includes training the hidden module using the sufficiently-labeled data, and subsequently, training the output module using a plurality of input examples each having an original label. The plurality of input examples may be a plurality of fully-labeled data. The method further includes automatically providing the resulting trained machine learning model for use in prediction tasks.

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First Claim