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Showing 1 to 3 of 3 for “"weighted loss function"”.
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Novel Instance-Level Weighted Loss Function for Imbalanced Learning
… minimize the binary cross-entropy objective function to determine the final parameter estimates. This objective function assumes an equal class distribution between the minority (i.e. events) and majority (i.e. non-events) classes, which almost never exists in real-world modeling. In the …
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Exploring Loss Functions in Machine Learning
<p>The loss function plays a critical role in machine learning. It is fundamental in training, evaluating, and optimizing machine learning models, directly impacting their effectiveness and efficiency in solving specific tasks. We explore three new loss functions and their applications. Softmax …
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Wireless Sensing and Fusion using Deep Neural Networks
… filters to provide an accuracy over 95%, and a weighted loss function to eliminate the underestimation error of model order. The improved MOE is shown improve subsequent array processing tasks such as reducing the overhead needed for temporal smoothing, reducing the search space for signal …