Hi All,
I have a very simple use case where I would like to predict a floating number (y), given four floating numbers (x1, x2, x3, x4) that denotes the property of a process. I would like to have some pointers or insights on different supervised and unsupervised approaches to solve this problem and which one among the two would be a better choice?
y - doesn’t have any range so far, and can be any floating value.
Example:
Training data:
x1 = 3758687 (throughput)
x2 = 2.8678 (latency)
x3 = 0.098 (loss)
x4 = 0 or 1 (binary)
y = {1.28,2.28,4.019,9.8,13,2}

now using this I need to create a model to be able to predict ‘y’.