Distance-Weighted Discrimination
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- Makoto Aoshima & Kazuyoshi Yata, 2019. "Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 473-503, June.
- Bolivar-Cime, A. & Marron, J.S., 2013. "Comparison of binary discrimination methods for high dimension low sample size data," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 108-121.
- Sungkyu Jung & Xingye Qiao, 2014. "A statistical approach to set classification by feature selection with applications to classification of histopathology images," Biometrics, The International Biometric Society, vol. 70(3), pages 536-545, September.
- Ishii, Aki & Yata, Kazuyoshi & Aoshima, Makoto, 2022. "Geometric classifiers for high-dimensional noisy data," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
- Jang, Hyun Jung & Shin, Seung Jun & Artemiou, Andreas, 2023. "Principal weighted least square support vector machine: An online dimension-reduction tool for binary classification," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
- Marron, J.S., 2017. "Big Data in context and robustness against heterogeneity," Econometrics and Statistics, Elsevier, vol. 2(C), pages 73-80.
- Makoto Aoshima & Kazuyoshi Yata, 2014. "A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 983-1010, October.
- Xiaosun Lu & J. S. Marron & Perry Haaland, 2014. "Object-Oriented Data Analysis of Cell Images," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 548-559, June.
- Anil K. Ghosh & Munmun Biswas, 2016. "Distribution-free high-dimensional two-sample tests based on discriminating hyperplanes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 525-547, September.
- Yugo Nakayama & Kazuyoshi Yata & Makoto Aoshima, 2020. "Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1257-1286, October.
- Makoto Aoshima & Kazuyoshi Yata, 2019. "High-Dimensional Quadratic Classifiers in Non-sparse Settings," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 663-682, September.
- Hayley Randall & Andreas Artemiou & Xingye Qiao, 2021. "Sufficient dimension reduction based on distance‐weighted discrimination," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1186-1211, December.
- Niladri Roy Chowdhury & Dianne Cook & Heike Hofmann & Mahbubul Majumder & Eun-Kyung Lee & Amy Toth, 2015. "Using visual statistical inference to better understand random class separations in high dimension, low sample size data," Computational Statistics, Springer, vol. 30(2), pages 293-316, June.
- Giuliodori, Andrea, 2009. "Clustering and classifying images with local and global variability," DES - Working Papers. Statistics and Econometrics. WS ws090101, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Sudhir Varma, 2020. "Blind estimation and correction of microarray batch effect," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
- Jung, Sungkyu, 2018. "Continuum directions for supervised dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 27-43.
- Tianxiao Sun & Ion Necoara & Quoc Tran-Dinh, 2020. "Composite convex optimization with global and local inexact oracles," Computational Optimization and Applications, Springer, vol. 76(1), pages 69-124, May.
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