Question

I´d like to use any technique of artificial inteligence to classify elements using several parameters. I have used artificial neural networks (ANN) to do it, with good results. My purpose now is to classify objects without using all the inputs parameters I have used to train my network. I mean:

Suppose I have trained my network with 10 parameters. Then, I´d like to test my network only with 3 parameters (different parameters for each instance). Can I do it with some kind of ANN, or is there another systems to do it?

(Numbers are only an example obviously)

I think my question is useful in many cases, because in some cases you may probably have many information from the past (in time), and you´d like to classify objects in the future time (and you cannot probably have enough information).

Answer 1

I think you need a recommender system. Systems like this are useful when dealing with lot of uncertain(or not known at all) data. There are many materials in web and literature that explains this topic well.

EDIT:
Very good explanation is provided by prof. Andrew Ng in https://www.coursera.org/course/ml

Based on comments, here are some guides:
xavier.amatriain.net/PFC/mramirez-recommender.pdf
infolab.stanford.edu/~ullman/mmds/ch9.pdf