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https://link.springer.com/article/10.1023%2FB%3AMACH.0000008082.80494.e0
Jan 01, 2004 · In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of equations in the dual space. While the SVM classifier has a large margin interpretation, …Cited by: 770
https://www.researchgate.net/publication/265108226_Benchmarking_Support_Vector_Machines
Although support vector machines are often considered to be the best classifiers currently available, random forests are strong competitors, frequently outperforming SVMs [8, 21]. The random ...
https://link.springer.com/chapter/10.1007/978-3-319-11218-3_22
Map-Reduce component of Hadoop performs the parallelization process which is used to feed information to Support Vector Machines (SVMs), a machine learning algorithm applicable to classification and regression analysis. ... Benchmarking Support Vector Machines Implementation Using Multiple Techniques. In: El-Alfy ES., Thampi S., Takagi H ...Cited by: 3
https://epub.wu.ac.at/1578/1/document.pdf
Support Vector Machines (SVM) are used for support vector C-classification with RBF kernel. [svm] Classification trees try to find an optimal partitioning of the space of possible observations, ... Benchmarking Support Vector Machines ...
https://www.g3journal.org/content/9/2/601
Feb 01, 2019 · A Benchmarking Between Deep Learning, Support Vector Machine and Bayesian Threshold Best Linear Unbiased Prediction for Predicting Ordinal Traits in Plant Breeding Osval A. Montesinos-López , Javier Martín-Vallejo , View ORCID Profile José Crossa , Daniel Gianola , Carlos M. Hernández-Suárez , Abelardo Montesinos-López , Philomin Juliana ...Cited by: 4
https://paperity.org/p/7521354/benchmarking-least-squares-support-vector-machine-classifiers
In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. ... Benchmarking Least Squares Support Vector Machine Classifiers, Machine Learning, 2004, pp. 5-32, Volume 54, Issue 1 ...Cited by: 770
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