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> Erkut Aykutlug and Mark Peng used XGBoost with creative feature engineering whereas AutoML uses both neural network and gradient boosting tree (TFBT) with aut
by ipsum2 7y ago
> Erkut Aykutlug and Mark Peng used XGBoost with creative feature engineering whereas AutoML uses both neural network and gradient boosting tree (TFBT) with automatic feature engineering and hyperparameter tuning.
It's hilarious that gradient boosted descent tree beat Google's fancy AutoML-generated neural networks.
- ptah 7y agoyes, and i bet they didn't use 2500 CPUs either
- jsty 7y agoGiven that 2500 n1-standard-1 preemptible instances in us-central-1 would cost a grand total of $25/hr, it's certainly not a 'must be Google or taller' requirement
- pplonski86 7y agoThe first thing is, the Neural Networks are not golden ML algorithm that is working always the best. I'm not surprised to see GBDT methods working better than NN. The NNs are very powerful because they can accept the wide-range of data types (tabular, images, voice) which is not possible with GBDT (maybe not yet). The second, I think architecture search fo NNs is very inefficient right now. Most of the methods are training new NN in every attempt. There is a lack for method that can start with any NN architecture and grow/prune it dynamically. Take a look at this poster, with dynamic topology adjustemnt for MLP http://www.ire.pw.edu.pl/~rsulej/NetMaker/icaisc/icaisc_poster.pdf http://www.ire.pw.edu.pl/~rsulej/NetMaker/icaisc/icaisc_post...
- mark_l_watson 7y agoYou might like AdaNet that doe’s architecture search in one TensorFlow session and seems efficient (at least my use of it).
- Tenoke 7y agoIm guessing 'creative feature engineering' vs 'automatic' suggests people were involved in it versus the completely end to end approach by AutoML. Im guessing that's the main reason they beat Google.
- mlthoughts2018 7y agoThat’s exactly what’s _not_ supposed to perform better than AutoML...
- faizshah 7y agoH2o's AutoML does GBM as well I think, I don't know if google's AutoML does.