classification feature selection I have a system which sends invitations to users to participate in online questionnaires and want to use machine learning in order to predict the likelihood of fulfilling the questionnaires in a predefined time ( i.e. within 1 day , 2 day , 3 days ,a week, 2 weeks, etc) based on various feature related to the users to whom the invitations are sent to , details of the questionnaires ( i.e. how long are they , their topic ,etc.) , other contextual data ( time of day , day of year , in which media the invitation are sent - i.e. sms / email etc). 
I can train with positive examples ( invitations that were responded to by users ) and negative examples ( invitations that WERE not responded to ) , however , I'm not sure how to take into consideration the "predefined time" into the feature vector. for example, should I simply include a feature of "days since invitation was sent" and in the positive examples include the time , and in negative examples replicate each example X each of the predefined times to indicate that the users didn't respond at all ?

Any advise would be welcome  !
You have a problem of data leakage.
The "days since invitation was sent" feature contains all the information on the concept. Therefore, adding it as a feature will prevent most common classifiers from using rules based on other features and will lead to misleading results.

Duplicating the negative row for each predefined time value will lead to a different distribution than the one you should be tested one, which need needles problems. 

Note that even that way, the feature might leak information (e.g., a small ratio of the positives will replay in two weeks while its distribution in the negatives will be higher, making it a good predicator for negative).

In case that you will have more complex representation of time (e.g., was the email sent on weekend? was the reply sent on weekend), the duplication of rows will be more complex.

I would try a different direction. It is likely that the negative rows has no influence on the time to reply in the positive ones. 
Therefore I would do a first research aimed to differ between replies and no replies without using the predefined time.

After that, do a second research only on the positives where the concept will be the predefined time, aiming to find what is influencing out given that the user had replied.