Localized Sliced Inverse Regression

Part of Advances in Neural Information Processing Systems 21 (NIPS 2008)

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Authors

Qiang Wu, Sayan Mukherjee, Feng Liang

Abstract

<p>We developed localized sliced inverse regression for supervised dimension reduction. It has the advantages of preventing degeneracy, increasing estimation accuracy, and automatic subclass discovery in classification problems. A semisupervised version is proposed for the use of unlabeled data. The utility is illustrated on simulated as well as real data sets.</p>