Results 11 to 20 of about 52,512 (299)
Mendel, 2023 Can machine learning take a prediction to win an investment in ICO (Initial Coin Offering)? In this research work, our objective is to answer this question. Four popular and lower computational demanding approaches including Ridge regression (RR),
Toai Kim Tran +6 more
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An identity for kernel ridge regression [PDF]
Theoretical Computer Science, 2010 35 pages; extended version of ALT 2010 paper (Proceedings of ALT 2010, LNCS 6331, Springer, 2010)
Fedor Zhdanov, Yuri Kalnishkan
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Treating Multicollinearity Problem Using Gool Programming Technique [PDF]
The Egyptian Statistical Journal, 2011 Multiple regression analysis is usually efficient for prediction, but often produces poor results because of the multicollinearity among the independent variables.
Afaf El-Dash +2 more
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Correlation Based Ridge Parameters in Ridge Regression with Heteroscedastic Errors and Outliers [PDF]
Journal of Statistical Theory and Applications (JSTA), 2015 This paper introduces some new estimators for estimating ridge parameter, based on correlation between response and regressor variables for ridge regression analysis.
A.V. Dorugade
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Low-Rank Tensor Thresholding Ridge Regression
IEEE Access, 2019 In the area of subspace clustering, methods combining self-representation and spectral clustering are predominant in recent years. For dealing with tensor data, most existing methods vectorize them into vectors and lose most of the spatial information ...
Kailing Guo +3 more
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Suggested Methods in Ridge Regression [PDF]
المجلة العراقية للعلوم الاحصائية, 2006 Three suggested procedures were adopted to determine the value of biasing parameter (k) in ridge regression: 1-fragmenting the ridge trace to groups each group contain semi-homogeneous absolute values of the estimated parameters, 2-rotating over the ...
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Mathematics, 2022 For the linear model Y=Xb+error, where the number of regressors (p) exceeds the number of observations (n), the Elastic Net (EN) was proposed, in 2005, to estimate b.
Rajaram Gana
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Logistic regression diagnostics in ridge regression
Computational Statistics, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Revan Özkale +2 more
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Adaptive ridge regression for rare variant detection. [PDF]
PLoS ONE, 2012 It is widely believed that both common and rare variants contribute to the risks of common diseases or complex traits and the cumulative effects of multiple rare variants can explain a significant proportion of trait variances.
Haimao Zhan, Shizhong Xu
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Another Look at Partitioned Ridge Regression Estimators [PDF]
The Egyptian Statistical Journal, 1992 Several biased estimators have been proposed as alternatives to the Least squares estimator when multicollinearity is present in the multiple linear regression model.
Linda Abskharoon, Mahmoud Mahmoud
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