I am kind of a newbie on machine learning and I would like to ask some questions based on a problem I have .
Let's say I have x y z as variable and I have values of these variables as time progresses like :
t0 = x0 y0 z0
t1 = x1 y1 z1
tn = xn yn zn
Now I want a model that when it's given 3 values of x , y , z I want a prediction of them like:
Input : x_test y_test z_test Output : x_prediction y_prediction z_prediction
These values are float numbers. What is the best model for this kind of problem? Thanks in advance for all the answers.
More details: Ok so let me give some more details about the problems so as to be more specific.
I have run certain benchmarks and taken values of performance counters from the cores of a system per interval.
The performance counters are the x , y , z in the above example.They are dependent to each other.Simple example is x = IPC , y = Cache misses , z = Energy at Core.
So I got this dataset of all these performance counters per interval .What I want to do is create a model that after learning from the training dataset , it will be given a certain state of the core ( the performance counters) and predict the performance counters that the core will have in the next interval.