How to use neural networks with large and variable number of inputs? I'm new to machine learning, but I have an interesting problem. I have a large sample of people and visited sites. Some people have indicated gender, age, and other parameters. Now I want to restore these parameters to each user.

Which way do I look for? Which algorithm is suitable to solve this problem? I'm familiar with Neural Networks (supervised learning), but it seems they don't fit.
There exist many possibilities for populating empty gaps on data.


Most repeated value: Fill the gaps with the most common value.
Create a distribution: Make the histogram and drop values according to that distribution.
Create a new label: Since you do not have information, do not assume any value and create another label/category to indicate that value is empty.
Create a classifier: Make a relation among the variable with empty gaps and the rest of the data and create a simple classifier. With this, populate the rest of the data.


There exist many others, but these are the most common strategies. My suggestion is not to populate and to keep unknown what is unknown.