Keras LSTM Paradigm
I'm not sure, but your batch_size could be set automatically, time_steps is equal to number of feature sets so for [[0.4, 0.8, -1]] its 1 for [[0.4, 0.8, -1],[1, 1.6, -0.2]] its 2 etc. Try to reshape your data to (shape[0],3).
I have a single time series that has multiple input features and a single output (classification). I would like to create a model that would predict the output at every step.
My data looks like this:
x: [[0.4, 0.8, -1], [1, 1.6, -0.2], ....]
y: [[1], [0], ...]
So when given a single feature vector, I would like my model to output 0 or 1. The feature vector is not a sequence of any kind, as this is just a straight-forward time series.
I have the following questions:

Since Keras requires data to be formatted in (batch_size, time_steps, num_features) and I have fixed num_features = 3, what should I put for batch_size and time_steps?
What do I put for the value of stateful? Since my data is in a specific order in that the first event in my list came first, followed by the second and third etc., I'm assuming I put stateful = True?