The invention discloses a ridge-regression-extreme-learning-machine-based local path planning method for an outdoor robot. The method comprises the following steps: step one, collecting environment information and extracting a region of interest by using a laser radar; step two, constructing a ...
This study proposed a spectral ensemble preprocessing method based on the rapidly developing ensemble learning methods in recent years and the ridge regression (RR) model, named stacking preprocessing ridge regression (SPRR), to address the aforementioned issues. Different from conventional ensemble ...
All data were centered before application of regression and CCA, as usual with these methods. 2 Perhaps because of this difference, the method in [27] did not perform well in our experiment, and we do not report its result in Sect. 6. 146 Y. Shigeto et al. Evaluation Criteria. The ...
the coefficients are displayed on the same scale. SeeRidge Regressionfor an example using a ridge trace plot, where the regression coefficients are displayed as a function of the ridge parameter. When making predictions, setscaledequal to0. For an example, seePredict Values Using Ridge Regression...
Ridge regression is a method for estimating coefficients of linear models that include linearly correlated predictors. Coefficient estimates for multiple linear regression models rely on the independence of the model terms. When terms are correlated and the columns of the design matrix X have an approx...
As we have shown before, both peptide-based regression models outperform the summarization-based approaches (21). Our RR method further improves on the LM model in comparison 6B-6A, in which the detection of DA is most challenging since it involves the two lowest spike-in concentrations. For ...
Ridge Regression is a methodology to handle the scenarios of the high collinearity of the predictor variables. This helps to avoid the inconsistancy.
(EMD). It is shown that the decomposition error tends to zero, as ensemble number increases to infinity in EEMD. In this paper, a novel EEMD-based ridge regression model (REEMD) is proposed, which solves the problem of mode mixing and achieves less decomposition error compared with the ...
岭回归法同时测定邻、间、对苯二酚2. Multi-factors Empirical analysis of health demands in china——Based on Ridge Regression; 影响我国医疗卫生需求的多因素实证分析——基于岭回归法3. The ridge regression method is applied to impedance inversion. 应用岭回归法对波阻抗反演进行了理论和应用研究。更多...
In this article, we propose a procedure to remedy this problem by the use of new ridge regression (RR) shrinkage parameterswhich we call the asymmetric interaction ridge (AIR) regression method. By means of Monte Carlo simulations we evaluate both OLS and AIR using the mean square error (MSE...