I have a problem where I have 9 data points that are collected every minute for 40 minutes, and, by the 40th minute, the solution would be either end up being black or white.
I would like to set up a neural network, which would take the live input of every minute; and I was hoping within the 25-30 minute mark to predict the outcome of what the results would be at 40 minute; which is a classification.
I have over 3000 historical runs of this experiment; each containing 40 rows of 9 columns data per experiment.
What network would I need to set up; so that it can learn from each run at every minute mark per experiment with the results; and then set it up for live input, when the experiment is running again.
I feel like I might need more than one system to accomplish this; any help in pointing me towards the right path would be greatly appreciated
I am using python (keras) to try to solve this problem.