Titlebook: Kernel Ridge Regression in Clinical Research; Ton J. Cleophas,Aeilko H. Zwinderman Textbook 2022 The Editor(s) (if applicable) and The Aut

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書目名稱Kernel Ridge Regression in Clinical Research影響因子(影響力)




書目名稱Kernel Ridge Regression in Clinical Research影響因子(影響力)學(xué)科排名




書目名稱Kernel Ridge Regression in Clinical Research網(wǎng)絡(luò)公開度




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書目名稱Kernel Ridge Regression in Clinical Research被引頻次學(xué)科排名




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書目名稱Kernel Ridge Regression in Clinical Research年度引用學(xué)科排名




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Kernel Ridge Regression (KRR),es are converted into discrete ones, otherwise discretized ones..Another problem is that of increasing mathematical complexity with multidimensional data. However, the . is an efficient and less computationally-intensive way to transform data into high dimensions. A third problem, is that of data ov

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Optimal Scaling vs Kernel Ridge Regression,ns, and performs even better than optimal scaling for the purpose of optimized predictive modeling..The traditional R Square values of the scale 1–3 models were respectively.The kernel ridge R Square values of the scale 1–3 models were respectively

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Effect on Being Blind of Age/Sex Adjusted Mortality of Onchocerciasis Patients in 12,816 Personyeare is 0,994, which means 94,4% certainty about the prediction of the outcome by the above three predictors. The presence of multicollinearity in the data was suspected, and confirmed as assessed with one-by-one linear regressions. Kernel ridge regression is a technique for analyzing multiple regressi

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Effect of Old Treatment on New Treatment, 35 Patients, Traditional Regressions vs Kernel Ridge Regrts was used as data example for testing the effects of simple linear regression, and quantile regression against kernel ridge regression. With traditional linear regression the old treatment was not a strong predictor of the new treatment with an overall R Square value of 0,219 (21,9% certainty abou

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Effect of Gene Expressions on Drug Efficacy, 250 Patients, Traditional Regressions vs Kernel Ridge bles regression showed that 6 genes were very significant independent predictors of drug efficacy scores. Kernel ridge regressions provided quite better datafit particularly.Much better statistics can thus be obtained with the help of kernel ridge regressions using one of the eight kernel density mo

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,Effect of Month on Mean C-Reactive Protein, 18?Months, Traditional Regressions vs Kernel Ridge Regrf paired differences between the first and subsequent monthly measures..The significant positive autocorrelations at the month no.13 (correlation coefficients of 0,42 (SE 0,14, t-value 3,0, p?