I am stuck in my data mining project. Actually, I don't know how to handle features that are not defined for some data. I try to explain better my situation. I am dealing with email data, and the problem is that some features are strictly related to email header field, so for example I extrapolate some informations from the Cc header field and, this header field is not always defined of course(and this is true for other fields as well). Now this means that the cell corresponding to this features for some data item will be missing, but actually it could not be considered as a missing value as it is not really something that is really missing. So I mean that it would not be correct to handle it using imputation. I though something like create multiple dataset based only on available features, but is there something already implemented about this in R or Weka tools? Or if someone know something better can please explain me how to solve this problem? Thanks in advance.