Web10. apr 2024 · In recent years, machine learning models have attracted an attention in solving these highly complex, nonlinear, and multi-variable geotechnical issues. Researchers attempt to use the artificial neural networks (ANNs), support vector machine (SVM) algorithms and other methods to solve such issues (Rukhaiyar et al. 2024; Huang et al. … Computing the (soft-margin) SVM classifier amounts to minimizing an expression of the form We focus on the soft-margin classifier since, as noted above, choosing a sufficiently small value for yields the hard-margin classifier for linearly classifiable input data. The classical approach, which involves reducing (2) to a quadratic …
Functional robust support vector machines for sparse and
Web24. júl 2016 · Sparse support vector machine (SVM) is a popular classification technique that can simultaneously learn a small set of the most interpretable features and identify the support vectors. It has achieved great successes in many real-world applications. Web4. sep 2014 · In this paper, we propose a sparse least square twin support vector machine with p norm named l p LSTSVM. Our new model is an adaptive learning procedure with l p … rv 50a plug vs dryer
Bridge seismic fragility model based on support vector machine …
WebBased on this sample library, seismic fragility curves based on support vector machines and relevance vector machines are established. To verify the effectiveness of the proposed method, the seismic fragility curves of the bridge system are established by the classic probit regression method, where probit regression can be subdivided into two ... Web24. mar 2024 · , On the sparseness and generalization capability of least squares support vector machines, J. Syst. Sci. Inf. 3 (2015) 279 – 288. Google Scholar; Yang et al., 2014 Yang L., Yang S., Zhang R., Jin H., Sparse least square support vector machine via coupled compressive pruning, Neurocomputing 131 (2014) 77 – 86. Google Scholar Web13. apr 2024 · In this paper, we introduce the idea of using additional features into robust energy-based least squares twin support vector machines (RELS-TSVM) and least … is ck one good