narx - inputs and targets
显示 更早的评论
In the NARX algorithm (Neural Net Toolbox), could someone explain what the difference between inputs and targets. I've read the manual, help guide, and have looked at the two arrays but still do not understand. Why would we include targets if this is what the algorithm is trying to predict?
Also is there a way to run a test case to via NARX and check prediction capability (R-squared...)?
Thank you so much for your help.
采纳的回答
Greg Heath
2016-6-24
You cannot build a successful net without knowing what transformation you want it to perform.
In general, inputs are typical examples from a known distribution or collection of inputs.
Targets are the known result of the transformation applied to specific inputs.
The purpose of the trained net is to be able to GENERALIZE, i.e., perform the transformation on arbitrary examples from the distribution or collection of examples.
I have posted zillions of examples using the collection of MATLAB examples obtained by using the commands
help nndatasets
doc nndatasets
Search BOTH the NEWSGROUP and ANSwERS using
greg narxnet tutorial
and
greg narxnet
Hope this helps
Thank you for formally accepting my answer
Greg
更多回答（0 个）
类别
在 帮助中心 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息
产品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
