My question basically is : in a learning problem, are there data sets that neural networks are not advised to be used ? What are some popular characteristics of such data sets?
The reason why I am asking is : In some articles it is proven that neural networks can learn any function. But are all the data sets represent a function? If they are not qualified to do so; what are the properties of unqualified data sets?
In my research I have difficulty in finding a good architecture and parameter combination. I am suspicious about the data set itself. Because I see the following pattern
Input1 Input2 Target 0.8 0.6 0.3 0.8 0.6 0.3 0.8 0.6 0.0 0.8 0.6 0.1
As a human I can not make a prediction about the target by looking at the inputs, and I expect that a neural network will not predict accurately as well. So may be some other approach is advised for such a case.