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I have a classification problem where I want to want to use probabilities instead of classes to train my model to learn to output probabilities. In my dataset, I have instances where the probabilities of two classes are almost equal and I would like the model to be able to learn these subtleties instead of me just providing the class for each instance. Is there an ML model that can handle this?

Thanks!

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    $\begingroup$ The standard cross entropy formulation works fine mathematically. If the implementation you use for the loss allows for soft labels, then this should work computationally as well. $\endgroup$ – GeoMatt22 Feb 24 at 5:56

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