Trained a time series neural network (NAR) with multiple inputs, now network requires multiple inputs to work/run. How do I train a time series neural network on multiple datasets, while keeping only 1 time series input to network

1 次查看（过去 30 天）
Daniel Borrus
Daniel Borrus 2018-11-14
I am trying to use a time series neural network (NAR) to predict stock prices.
I would like to train the network on different stocks, say 5 different stocks. And I have say 100 time steps. So I created a matrix with 100 rows and 5 columns. I then trained a NAR neural network on the dataset.
Now I want to see what the network will predict if I give it some data on a new stock. But, it seems to me like my network is expecting 5 inputs. That's not what I wanted. I just wanted to give the network 5 different datasets to train on, not use them all together to predict the next 5 prices.
Am I understanding my network correctly? Does it truly require 5 inputs? Or is there an option to change it back to one input, now that it has been trained.
If not, is there a way to train a network on mulitple inpedendent data sets?
Thanks!
- Dan

请先登录，再回答此问题。

回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

标签

产品


版本

R2018b

Community Treasure Hunt

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

Start Hunting!

Translated by