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neural network loss function criterion

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Deep Neural Network Loss Function Criterions

#artificialintelligenceNov-17-2021, 00:45:27 GMT

In our deep learning model, depending on whether we are doing classification or regression tasks, we have to define a loss function that compares the predicted result vs the expected result (labeled data). In classification problems, the loss function calculates the loss for misclassifications. Cross-Entropy Loss measures the performance of classification. It is a combination of the Negative Log-Likelihood Loss (NLL) and Softmax. Some of the most used loss functions for regression tasks are L1 loss, MSE (L2 loss), and Smooth L1 Loss.

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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)

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