How to train a time series dataset ?
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I have a data set with 2 columns (the first column is related to currents of a battery and the second column indicates the time seconds correspond to the current). what I want to do is training the currents data according to the time (second columns).I convert my data set in form of time-series object:
(ts = timeseries(datavals,timevals)). And now I want to train this object. However I am not sure whether it is possible or not and how can I do it.
I would appreciate any further help.
More Answers (3)
Edited: Majid Farzaneh on 23 May 2018
Hi, what's your purpose for training this data? A neural network can predict something for you. For example you can train the network by current as input and time as output, then use the network, give a current to it and it provides a time for you. This is a single input/ single output network and you can use a feedforwardnet like this:
net=feedforwardnet(10); % 10 is number of neurons in the first layer
Now you have a trained network and you can use it like this:
Greg Heath on 23 May 2018
Edited: Greg Heath on 23 May 2018
Consider current as a function of time.
The rest should be straightforward using FITNET.
HOWEVER, YOU HAVE USED THE TERM TIMESERIES. THIS COULD IMPLY THAT EACH POINT BEYOND THE ITH DEPENDS ON THE PREVIOUS I VALUES AND NOT NECESSARILY EXPLICITLY ON TIME.
Thank you for formally accepting my answer