Applying custom costfunction in TensorFlow's SKFlow model training

Question

I'm trying to make a regression model with TensorFlow while using the sklearn implementation so it plays nicely with all the other models I've made. However I cannot seem to find a way to train the model with a custom score function (cost function or objective function).

Is this simply impossible with skflow?

Thanks loads!

Answer 1

Many of the examples uses learn.models.logistic_regression, which is basically a built-in high-level model that returns predictions and losses. For example, models.logistic_regression uses ops.losses_ops.softmax_classifier, which means you can look into how ops.losses_ops.softmax_classifier is implemented and implement your own loss function using perhaps TensorFlow low-level APIs.