Weighted cross entropy loss formula

Returns A Tensor of the same shape as logits with the componentwise weighted logistic losses.

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ValueError If logits and labels do not have the same shape. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4. For details, see the Google Developers Site Policies.

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Cross-Entropy Loss Log-likelihood Perspective

TensorFlow Lite for mobile and embedded devices. TensorFlow Extended for end-to-end ML components.


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TensorFlow r2. Pre-trained models and datasets built by Google and the community. Ecosystem of tools to help you use TensorFlow. If given, has to be a Tensor of size nbatch.

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Must be a vector with length equal to the number of classes. For a binary classification, you would often hear positive and negative example, which would represent the classes 1 and 0, respectively. Thanks, but that was not what I was looking for.

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To be more clear, can you give me example to calculate weights for multilabel case. In that situation what should be the process to calculate pos weights that can be used in loss function? Sorry, the last bit is confusing. Can you elaborate?