Transductive Inference for Estimating Values of Functions

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

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Olivier Chapelle, Vladimir Vapnik, Jason Weston


We introduce an algorithm for estimating the values of a function at a set of test points Xe+!, ... , xl+m given a set of training points (XI,YI), ... ,(xe,Ye) without estimating (as an intermediate step) the regression function . We demonstrate that this direct (transduc(cid:173) ti ve) way for estimating values of the regression (or classification in pattern recognition) can be more accurate than the tradition(cid:173) alone based on two steps, first estimating the function and then calculating the values of this function at the points of interest.