CODEWITHSUNDEEP
tensorflow
Jacob B
Jacob B

Reputation: 724

How to use tensorflow pairwise loss

In tensorflow, there is a pairwise mean squared error function which takes in "predictions" it is not documented if this should be a sigmoid/softmax output or logits. https://www.tensorflow.org/api_docs/python/tf/losses/mean_pairwise_squared_error

I am looking to see if predictions must be a certain form for the input, or if there is a better pairwise loss function available.

Upvotes: 1

Views: 399

Answers (1)

gorjan
gorjan

Reputation: 5555

The logits layer, in deep learning context is the layer on which the softmax function is applied. The softmax function is applied when want to perform multi-class classification. When we want to perform classification, the most common error measure is cross-entropy. On the other hand, the mean pairwise squared error is used in the context of regression. When we perform regression, we want to predict a real value as opposed to classification when we want to predict a class. With that said, the layer that will generate the outputs won't be a logits layer, but an ordinary linear layer. Moreover, the most common error measure when you want to perform regression is mean squared erorr.

Upvotes: 0

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