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Deep Learning > link > Can Deep Learning (and Neural Networks) be useful for regression problems where the output variable has an unknown (or varying in real time) upper bound?

Deep Learningで学習を検討しているのは「多クラス分類」ではなく「回帰」。



Vicent Ribas Ripoll, I solve classification problems.
Written Aug 16, 2013

Yes they are. One only has to make sure to use the proper cost function (MSE) and adapt the network to provide a continous output (this normally means removing the softmax in the output). Some examples are:

Page on Stanford

上記のPDFファイルではPower Loadという多数の山と谷を持つ形状の学習をしている。

Learning Method %RMSE
Kernelized Regression 8.3%
Frequency NN 6.7%
Deep Feedforward NN 5.9%
Deep Recurrent NN 2.8%

自分が必要な精度(system of linear equationの初期値の誤差)がどれくらいのものかは実際に実験をしないと分からない。

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