Keras. Correct way to give a (x,y) plot + features as input to a NN
If x coordinates for all plots are same you could (and in fact should) ignore it. Because in this case this data do not introduce any additional information. Their use will only lead to a more complex neural network, worse convergence and as result to increasing of training time and performance degradation.
About second question - it is not necessary to do it. During training neural network will automatically identify which features are the most important.
Currently I'm trying to make Keras binary classify a set of (x,y) plots.
As a newbie, I can't figure out the proper way to give a correct input, since I've got these plots with app 3400 pairs each one and a set of 8 aditional features (local minimae locations) for every plot. What I tried is to give keras a 3400 + 3400 + 8 input layer, but it just feels wrong to do, and so far isn't making any progress.
As x variable is almost a correlative order, ¿should I ignore it?
¿Is it possible to ask keras to distinguish: "Hey these 3400 numbers are a plot, and these other 8 are some features about it"?