How to use scikit-learn metrics in CNTK?
Unless this metric is already implemented in CNTK, implement your own custom "metric" function in whatever format CNTK requires, and have it pass the inputs on to scikit-learn's metric function.
I wish to use classification metrics like matthews_corrcoef as a metric to a neural network built with CNTK. The way I could find as of now was to evaluate the value by passing the predictions and label as shown
matthews_corrcoef(cntk.argmax(y_true, axis=-1).eval(), cntk.argmax(y_pred, axis=-1).eval())
Ideally I'd like to pass the metric to the trainer object while building my network.
One of the ways would be to create own custom metric and pass that to the trainer object. Although possible, it'll be better to be able to reuse the already existing metrics present in other libraries.