# Infer dependent variables to produce output aligned to trained data

Hypothetical example, say I wanted: P(gender,ethnicity|age,hair); so that the input would aligned to a trained dataset of: (gender,ethnicity,age,hair) => hat bought.

What approach is 'best' for computing ~gender and ~ethnicity given age,hair; in order to predict the hat bought?

The processing of the inputs => hat can be done/learned offline whereas infering the missing input values shall be done online. The results of the online pass shouldn't be stored in the network.

FYI: I am considering two Recurrent Neural Networks one for each problem.

• Hmm, looks like what I'm talking about is called Imputation – A T Feb 8 '17 at 4:48