Transductive Inference for Estimating Values of
Functions
Olivier Chapelle, Vladimir N. Vapnik and Jason Weston
Abstract: We introduce an algorithm for estimating the values of
function on specific points
given a set of training points
without estimating (as an intermediate step) the regression
function. We demonstrate that this direct (transductive) way for
estimating values of regression (or classification in pattern
recognition) is more accurate than the traditional one based on two
steps, first estimating the function and then calculating the
values of this function at the point of interest.
given a set of training points
without estimating (as an intermediate step) the regression
function. We demonstrate that this direct (transductive) way for
estimating values of regression (or classification in pattern
recognition) is more accurate than the traditional one based on two
steps, first estimating the function and then calculating the
values of this function at the point of interest.