3 ms·
Not only will they work just fine, they'll save you compute costs, training time and lower your need for data.
by carlmr 5y ago
Not only will they work just fine, they'll save you compute costs, training time and lower your need for data.
- periheli0n 5y agoNot to mention the shedloads of “X is all you need” papers which you can ignore, because Bishop’s “Pattern Recognition and ML” book is actually all you need (plus perhaps a good reference on linear algebra).
- A-Train 5y agoNot necessarily true that MLPs are very compute expensive. It is maximum a couple of layers and if your input is sparse (categorical) you can gain even more. For some problems it can be the fastest and decent non linear model from my experience.
- periheli0n 5y agoI don’t think that was the claim… MLP/ANNs are fine except for the difficulties around interpretability. DTs and LR are preferable on that front. Or an SVM if you know a kernel/similarity metric that kills it in your data.