SUPPORT VECTOR REGRESSION FOR CENSORED DATA

摘要

A method of producing a model for use in predicting time to an event includes
obtaining mufti-dimensional, non-linear vectors of information indicative of
status of multiple test subjects, at least one of the vectors being right-
censored, lacking an indication of a time of occurrence of the event with
respect to the corresponding test subject, and performing regression using the
vectors of information to produce a kernel-based model to provide an output
value related to a prediction of time to the event based upon at least some of
the information contained in the vectors of information, where for each vector
comprising right-censored data, a censored-data penalty function is used to
affect the regression, the censored-data penalty function being different than
a non-censored-data penalty function used for each vector comprising
noncensored data.