Pyhton, Keras, SciKit-Learn, Matplotlib: Machine learning research project around classification of intent behind tech support emails in order to enable automatic follow up.
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How to improve cross validation by selecting folds #28
Optimisation of cross validation:
I'm confident I can optimise cross validation folds by looking for the smoothest curve on graphs of the k parameter of the K-Nearest Neighbours classifier versus accuracy, when varying the number of folds between graphs. Although a more mathematical approach would be preferable. I have struggled to find instances of cross validation for neural networks - do you know of any good examples?
https://stats.stackexchange.com/questions/27730/choice-of-k-in-k-fold-cross-validation