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CALIBRATING RELIABILITY OF MULTI-LABEL CLASSIFICATION NEURAL NETWORKS
CALIBRATING RELIABILITY OF MULTI-LABEL CLASSIFICATION NEURAL NETWORKS
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机译:校准多标签分类神经网络的可靠性
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摘要
Methods, systems, and computer-readable storage media for tuning behavior of a machine learning (ML) model by providing an alternative loss function used during training of a ML model, the alternative loss function enhancing reliability of the ML model, calibrating the confidence of the ML model after training, and reducing risk in downstream tasks by providing a mapping between the confidence of the ML model to the expected accuracy of the ML model.
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