title: Least-squares two-sample test.
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).
authors.affiliation: Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, Japan. sugi@cs.titech.ac.jp
authors.forename: Masashi
authors.initials: M
authors.lastname: Sugiyama
authors.forename: Taiji
authors.initials: T
authors.lastname: Suzuki
authors.forename: Yuta
authors.initials: Y
authors.lastname: Itoh
authors.forename: Takafumi
authors.initials: T
authors.lastname: Kanamori
authors.forename: Manabu
authors.initials: M
authors.lastname: Kimura
mesh_terms: D000465:Algorithms; D016018:Least-Squares Analysis