http://swrc.ontoware.org/ontology#TechnicalReport
Conditional Density Estimation Based on Density Ratio Estimation
en
Tokyo Institute of Technology / Japan Science and Technology Agency
Nagoya Institute of Technology
The University of Tokyo
Nagoya University
Tokyo Institute of Technology
The University of Tokyo
Masashi Sugiyama
Ichiro Takeuchi
Taiji Suzuki
Takafumi Kanamori
Hirotaka Hachiya
Daisuke Okanohara
Estimating the conditional mean of an input-output relation is the goal of regression. However, regression analysis is not sufficiently informative if the conditional distribution has multi-modality, is highly asymmetric, or contains heteroscedastic noise. In such scenarios, estimating the conditional distribution itself would be more useful. In this paper, we propose a novel method of conditional density estimation that is suitable for multi-dimensional continuous variables. The basic idea of the proposed method is to express the conditional density in terms of the density ratio and the ratio is directly estimated without going through density estimation.
Estimating the conditional mean of an input-output relation is the goal of regression. However, regression analysis is not sufficiently informative if the conditional distribution has multi-modality, is highly asymmetric, or contains heteroscedastic noise. In such scenarios, estimating the conditional distribution itself would be more useful. In this paper, we propose a novel method of conditional density estimation that is suitable for multi-dimensional continuous variables. The basic idea of the proposed method is to express the conditional density in terms of the density ratio and the ratio is directly estimated without going through density estimation.
AA12055912
研究報告バイオ情報学（BIO）
2009-BIO-19
4
1-8
2009-12-10