Zobrazeno 1 - 10
of 321
pro vyhledávání: '"Shinto Eguchi"'
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract Nonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-
Externí odkaz:
https://doaj.org/article/894b93dc70be47c9b2221d800da7711f
Autor:
Katsuhiro Omae, Shinto Eguchi
Publikováno v:
BMC Medical Research Methodology, Vol 20, Iss 1, Pp 1-12 (2020)
Abstract Background To accurately predict the response to treatment, we need a stable and effective risk score that can be calculated from patient characteristics. When we evaluate such risks from time-to-event data with right-censoring, Cox’s prop
Externí odkaz:
https://doaj.org/article/cb99a270410b49b4a87c593b157d713f
Publikováno v:
Total Quality Science. 8:1-13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0bbc33e163a431eaadc71246bd1dc51
https://doi.org/10.17929/tqs.8.1
https://doi.org/10.17929/tqs.8.1
Publikováno v:
International Journal of Mathematics for Industry, Vol 11, Iss 1, Pp 1950002-1-1950002-10 (2019)
In this paper, as data, ellipsoids in a color coordinate called the Commission Internationale de l’Eclairage (CIE)-Lab system are given as data for 19 colors. Each ellipsoid is a region where all points are visually recognized as the same color at
Externí odkaz:
https://doaj.org/article/9c3965c180a4466fb209437f16f19e18
Publikováno v:
Quality Innovation Prosperity / Kvalita Inovácia Prosperita; 2024, Vol. 28 Issue 1, p1-14, 14p
Publikováno v:
BMC Bioinformatics, Vol 18, Iss 1, Pp 1-15 (2017)
Abstract Background Linear scores are widely used to predict dichotomous outcomes in biomedical studies because of their learnability and understandability. Such approaches, however, cannot be used to elucidate biodiversity when there is heterogeneou
Externí odkaz:
https://doaj.org/article/151d98e133b74a289fd79f277dd5661f
Publikováno v:
Japanese Journal of Statistics and Data Science.
We discuss species distribution models (SDM) for biodiversity studies in ecology. SDM plays an important role to estimate abundance of a species based on environmental variables that are closely related with the habitat of the species. The resultant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ffe57e12e818f6561dc3a24b4bad34d
https://doi.org/10.1007/s42081-023-00206-1
https://doi.org/10.1007/s42081-023-00206-1
Autor:
Osamu Komori, Shinto Eguchi
Publikováno v:
Entropy, Vol 23, Iss 5, p 518 (2021)
Clustering is a major unsupervised learning algorithm and is widely applied in data mining and statistical data analyses. Typical examples include k-means, fuzzy c-means, and Gaussian mixture models, which are categorized into hard, soft, and model-b
Externí odkaz:
https://doaj.org/article/4291268da60b4c50a5e7db5942c46afd
Publikováno v:
Entropy, Vol 17, Iss 8, Pp 5673-5694 (2015)
In this paper, we investigate the basic properties of binary classification with a pseudo model based on the Itakura–Saito distance and reveal that the Itakura–Saito distance is a unique appropriate measure for estimation with the pseudo model in
Externí odkaz:
https://doaj.org/article/41c4a7329be84343b7f879df451a242c
Autor:
Hideitsu Hino, Shinto Eguchi
Publikováno v:
Information Geometry.
Active learning is a widely used methodology for various problems with high measurement costs. In active learning, the next object to be measured is selected by an acquisition function, and measurements are performed sequentially. The query by commit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65c8aec937b974dd2aed85e9ef74c14f
https://doi.org/10.1007/s41884-022-00081-x
https://doi.org/10.1007/s41884-022-00081-x