I built a MLP for classification problem. I used KDD99 dataset. but the problem is that when I run it it gives ech time a different value of accuracy. Is this logic? I mean could the same model for the same data gives each time a different value of accuracy? if so why?
I assume by "run" you mean training run. Different training runs can have different performances due to many factors:
- Different random initialization.
- Different data sampling because of stochastic gradient descent (SGD).
- Stopping in different local minima.
- Stopping training before asymptotic performance.