I'm currently sitting on a problem, where i'm uncertain if there is not a much simpler solution.
I'm trying to train a DNN with a dataset for a classification task that should be cost sensitive. Classic literature on this kind of task use a cost weight that is constant for any kind of misclassification. My problem needs to use one of the dimensions of the input as the cost of misclassification for that single classification.
My solution would be to use TensorFlow and add the parameter i later need to a collection and then write a custom loss function where i grab the values from the collection for my cost sensitive loss.
So my question would be, does anybody know of any simpler solution, open source implementation etc.?