# How to make a Neural network understand that multiple inputs are related (to the same entity)?

I am not sure if this is the right place to ask this but here goes:

Sometimes times two or more inputs of a neural networks can often be related to a single "real world" entity.

E.g : Height and weight of a person to predict the probability of disease in population or price and volume of a stock to predict the market.

When a single training set contains data about a number of these entities, how can we make a neural network understand that two inputs (or more) are related to the same entity?

Amongst all the people I have asked, the general consensus seems to be:

• Neural Networks do not work this way
• It is not possible
• Such a grouping of data is not required
• Neural Networks are supposed to find the relationship amongst inputs, you are not supposed to feed it the relationships
• The training data set need to be reworked / reconfigured
• I have never heard of such a thing

So, obviously this is not in the mainstream. Has anyone heard of any research in this direction?

P.S. If you agree with the above opinion (it can't / shouldn't be done) please provide a reason why.

• The fact that the values appear in the same input vector already conveys the information that they correspond to the same instance (entity). – alto Jan 13 '14 at 16:07
• But what happens when we have the data of a population of entities to predict something about the entire population? See my (edited) eg. – Shayan RC Jan 13 '14 at 16:12
• You'll need to add more details as there are several different ways one could approach such a problem. The most important issue would probably be if the size of the population you want to make a prediction about is fixed or not. – alto Jan 13 '14 at 16:21
• I'm trying to predict stock market crashes using a neural network but I was hoping for general answer. In this case the population size is fixed. – Shayan RC Jan 13 '14 at 16:27
• You can use a network that isn't fully connected until the end result is calculated. Certain inputs get connected together down one path, while other inputs are connected down a different path, and then they fully connect to get a result. – Frobot Mar 30 '16 at 3:48