Výsledky vyhledávání - "Myoungshic Jhun"

Hierarchically penalized support vector machine with grouped variables

Autor: Myoungshic Jhun, Jongkyeong Kang, Eunkyung Kim, Sungwan Bang

Publikováno v: International Journal of Machine Learning and Cybernetics. 8:1211-1221

When input features are naturally grouped or generated by factors in a linear classification problem, it is more meaningful to identify important groups or factors rather than individual features. The F ∞-norm support vector machine (SVM) and the g

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b0585018f5598496f09c782aea448749
https://doi.org/10.1007/s13042-016-0494-2

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Composite kernel quantile regression

Autor: Myoungshic Jhun, Sungwan Bang, Soo-Heang Eo, HyungJun Cho

Publikováno v: Communications in Statistics - Simulation and Computation. 46:2228-2240

The composite quantile regression (CQR) has been developed for the robust and efficient estimation of regression coefficients in a liner regression model. By employing the idea of the CQR, we propose a new regression method, called composite kernel q

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::71d4b147711c811eb1611b63cbcce9c0
https://doi.org/10.1080/03610918.2015.1039133

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Applications of Bootstrap Methods for Canonical Correspondence Analysis

Autor: Hyeon-Seok Ko, Hyeong Chul Jeong, Myoungshic Jhun

Publikováno v: Korean Journal of Applied Statistics. 28:485-494

Canonical correspondence analysis is an ordination method used to visualize the relationships among sites, species and environmental variables. However, projection results are fluctuations if the samples slightly change and consistent interpretation

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9713a4fc77cc4a272dd2bd618576fe0b
https://doi.org/10.5351/kjas.2015.28.3.485

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Weighted L1-Norm Support Vector Machine for the Classification of Highly Imbalanced Data

Autor: Myoungshic Jhun, Eunkyung Kim, Sungwan Bang

Publikováno v: Korean Journal of Applied Statistics. 28:9-21

The support vector machine has been successfully applied to various classiﬁcation areas due to its ﬂexibilityand a high level of classiﬁcation accuracy. However, when analyzing imbalanced data with uneven classsizes, the classiﬁcation accurac

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::db89ff35f127207daa8aa26966eaa6f8
https://doi.org/10.5351/kjas.2015.28.1.009

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A Comparison Study for Ordination Methods in Ecology

Autor: Hyeon-Seok Ko, Hyeong Chul Jeong, Myoungshic Jhun

Publikováno v: Korean Journal of Applied Statistics. 28:49-60

Various kinds of ordination methods such as correspondence analysis and canonical correspondence analysisare used in community ecology to visualize relationships among species, sites, and environmental variables.Ter Braak (1986), Jackson and Somers (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::63b18583d2df611ea2c4f2795102e474
https://doi.org/10.5351/kjas.2015.28.1.049

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