Re:Deep Learning’s Impact on Image Processing, Mathematics, ...
by gaius on Sunday May 07, 2017 @06:30AM
(#14284771)
Deep learning does not have a special relationship to overfitting
Yes and no. Let's say you have a time series and you know there is some pattern in it and you are interested in predicting what it will be at time t. A Fourier analysis would give you a formula to plug numbers into that anyone can understand. NN or DL might give you as good, or accounting for noise, even a slightly better prediction when backtested but now you need to explain "why did it do this" - to a financial regulator who is looking at insider trades, or a commission looking into why a piece of equipment failed killing the user (say, a self-driving car), or a newspaper who's noticed more people of race X are being turned down for mortgages. That's why I say it is dependent on the application of the algo.
Yes and no. Let's say you have a time series and you know there is some pattern in it and you are interested in predicting what it will be at time t. A Fourier analysis would give you a formula to plug numbers into that anyone can understand. NN or DL might give you as good, or accounting for noise, even a slightly better prediction when backtested but now you need to explain "why did it do this" - to a financial regulator who is looking at insider trades, or a commission looking into why a piece of equipment failed killing the user (say, a self-driving car), or a newspaper who's noticed more people of race X are being turned down for mortgages. That's why I say it is dependent on the application of the algo.