Do you have any advice on how to increase performance of NN? Id be interested to see some examples of NN doing better than lgbm benchmark on medium size tabular data. What black magic is needed to achieve this? Would be super valuable to my job:)
This tuning approach gets good results for Lightgbm. I'd recommend using TimeSeriesSplit.
I've seen colleagues do something like this, or random search over NN architecture (NUM layers, nodes per layer, learning rate, dropout rate), always falling short of results this archives, despite far longer time to code up an tune model.
This tuning approach gets good results for Lightgbm. I'd recommend using TimeSeriesSplit.
https://www.kaggle.com/nanomathias/bayesian-optimization-of-...
I've seen colleagues do something like this, or random search over NN architecture (NUM layers, nodes per layer, learning rate, dropout rate), always falling short of results this archives, despite far longer time to code up an tune model.