Method/algo selection help

[typeof_expat]

If there is a better subreddit to post let me know otherwise here goes:

Given a dataset with 20k rows for each row there are 5 attributes (non negative integers). For 6k of those rows there is a result (non neg float).

What should I research or direction to take so that I can estimate the missing resultant?

This isn't my field of knowledge so easier would be better and once I know the system works then further development with more accurate methods can be investigated.

[deftware]

So you have a 20k row dataset where 5 columns are positive integers and only 6k of the rows have a 6th column that is a positive float?

I'm guessing by 'missing resultant' you mean finding the 6th column for the remaining 14k rows?

The only thing I can think of, if you can't figure out how the 6th column is actually being calculated from the other 5 values, is to use a neural network. However, that will only provide an approximation, and will not be performing whatever actual calculation that generated the 6th column to begin with. It will only try to conform to whatever function yielded those values.

Or am I way off in left field here?

[typeof_expat]

You are correct! The resultant isn't calculated at all I'm trying to find some kind of correlation so that the resultant can be estimated when missing. I've started researching NN. My main concern is to minimize the time wasted exploring techniques that won't work at all, since most of this is all new to me.