Least-squares two-sample test |
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Authors: | Masashi Sugiyama Taiji Suzuki |
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Affiliation: | a Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, Japanb PRESTO, Japan Science and Technology Agency (JST), Japanc The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japand Nagoya University, Furocho, Chikusaku, Nagoya 464-8603, Japan |
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Abstract: | The goal of the two-sample test (a.k.a. the homogeneity test) is, given two sets of samples, to judge whether the probability distributions behind the samples are the same or not. In this paper, we propose a novel non-parametric method of two-sample test based on a least-squares density ratio estimator. Through various experiments, we show that the proposed method overall produces smaller type-II error (i.e., the probability of judging the two distributions to be the same when they are actually different) than a state-of-the-art method, with slightly larger type-I error (i.e., the probability of judging the two distributions to be different when they are actually the same). |
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Keywords: | Two-sample test Homogeneity test Density ratio estimation Unconstrained least-squares importance fitting Pearson divergence |
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