Why can't I use the mae error with the Levenber-Marquardt algorithm?

1 次查看（过去 30 天）
Giuseppe D'Amico
Giuseppe D'Amico 2020-12-4
评论： Giuseppe D'Amico 2020-12-4
Hi, I'm training a neural network using a script I got using the matlab tool on neural networks.In particular I am using a timedelaynetwork for the prediction of a historical power series, I modified the network by inserting two hidden layers, one with a logsig activation function and one with a tansig activation function.I am using is the levenberg-marquardt, inserting the mae as a performance function, the message in the figure appears in the command window.
Why can't I use the mae with the trainlm?
Also, I would like to ask you, in your opinion is the architecture and type of network I am using to make the power prediction correct? or could it be improved in some way?

请先登录，再回答此问题。

采纳的回答

Matt J
Matt J 2020-12-4
编辑：Matt J 2020-12-4
Why can't I use the mae with the trainlm?
Just a guess, but Levenberg-Marquardt presumes that a Jacobian can be computed at the optimum parameter selection. In the ideal scenario where the optimal MAE=0, the Jacobian would fail to exist, due to the non-differentiability of at .
  3 个评论
显示 1更早的评论
Matt J
Matt J 2020-12-4
Couldn't you just use trainNetwork, say with its default stochastic gradient descent algorithm?
Giuseppe D'Amico
Giuseppe D'Amico 2020-12-4
I have never used it, would it be okay to use the trainNetwork function to train a network needed to predict a power time series?

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by