採用された回答

Greg Heath
Greg Heath 2013 年 12 月 2 日

2 投票

[x,t] = simplefit_dataset;
net = fitnet(4);
rng(0)
[ net tr y e ] = train(net,x,t);
biaserr = mean(e(:))
varerr = var(e(:))
HTH
Thank you for formally accepting my answer
Greg

2 件のコメント

SAM
SAM 2017 年 10 月 13 日
hi Greg, how can I calculate bias and variance if I have mean square error ? or i must have err=Targets-predictions
Muhammad Adil Raja
Muhammad Adil Raja 2018 年 12 月 8 日
Hi Greg, I really like this definition of variance as it is calculated over the error and not on the model output alone. However, is there a reference to back it up? Normally the variance is defined as the variance of the model output, which rather sounds non-sensible to me.
Moreover, how to compute these values if I am using fitnet for MIMO (multiple input or multiple output) problems or while using ensembles?
Best,
MA

サインインしてコメントする。

その他の回答 (1 件)

Mohamad
Mohamad 2013 年 12 月 2 日

0 投票

Greg Thank you very much.

カテゴリ

ヘルプ センター および File Exchange で Deep Learning Toolbox についてさらに検索

Community Treasure Hunt

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

Start Hunting!

Translated by