Can cosine similarity be objective function for deep learning?

Question

I want to train an output vector(which is from deep learning model) like fixed vector. Hence, I chose a cosine similarity between two vectors as the objective function. However, I don't know if that is a correct approach for my need.

In order to contribute, we need sample code of what you are working with in order to weight in or propose alternatives. — SeeDerekEngineer, Jul 24 '17 at 02:34

score 1 · Accepted Answer · answered Jul 24 '17 at 08:20

No. The cosine similarity is a measure of how similar two items (samples in your dataset) are.

In contrast, the objective function when training a neural network should be a definition of the current estimation error over the data - so they are different things.

Can cosine similarity be objective function for deep learning?

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