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Why there is a - in front of the regression_loss? #15

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Wang-Yu-Qing opened this issue Jul 27, 2024 · 0 comments

Wang-Yu-Qing commented Jul 27, 2024

in zero_inflated_lognormal.py line 76:

      regression_loss = -tf.keras.backend.mean(
      positive * tfd.LogNormal(loc=loc, scale=scale).log_prob(safe_labels),
      axis=-1)

     return classification_loss + regression_loss

In the paper, the Loss equals CrossEntropyLoss + LogNormalLoss, so why there is a minus in front of the LogNormalLoss?

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