model.
For this I need to provide class prediction logits as targets and use crossentropy as the loss.
I'm not sure how to proceed with this in catboost. The test code I tried out says that I HAVE to provide class labels only and cannot provide logits for the targets.
Is this something that can be done in catboost or do I need to implement a custom loss function that calculates crossentropy and use a regressor?
Hello! You can just use loss_function='CrossEntropy' https://catboost.ai/en/docs/concepts/loss-functions-classification#CrossEntropy
That works normally but i have to provide classes as 0/1 labels of i do that. What i want to provide is target logits for the label instead of the classic 0/1. So 0.996 as target instead of 1
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