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Least-squares two-sample test
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DOI：10.1016/j.neunet.2011.04.003.png)
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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). (C) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Two-sample test
Homogeneity test
Density ratio estimation
Unconstrained least-squares importance fitting
Pearson divergence
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