A New Approach for Bias–Variance Analysis Using Regularized Linear Regression-Reference-Cited by-同舟云学术

A New Approach for Bias–Variance Analysis Using Regularized Linear Regression

Published:2019-10-31 Issue: Volume: Page:35-46
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
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Author:

Reddy M. Rajasekhar,Kumar B. Nithish,Rao N. Madhusudana,Karthikeyan B.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0339-9_4

Reference10 articles.

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4. A. Jovanovich, A. Lazar, Comparison of optimization methods for l1-regularized logistic regression. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.2562

5. A.F. Schmidt, R.H. Groenwold, M.J. Knol, A.W. Hoes, M. Nielen, K.C. Roes, A. De Boer, O.H. Klungel, Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study. J. Clin. Epidemiol. 67(7), 821–829 (2014)

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