A study on the error of distributed algorithms for big data classification with SVM
Wang, Cheng ; Cao, Feilong
ANZIAM Journal, Tome 58 (2017), / Harvested from Australian Mathematical Society
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The error of a distributed algorithm for big data classification with a support vector machine (SVM) is analysed in this paper. First, the given big data sets are divided into small subsets, on which the classical SVM with Gaussian kernels is used. Then, the classification error of the SVM for each subset is analysed based on the Tsybakov exponent, geometric noise, and width of the Gaussian kernels. Finally, the whole error of the distributed algorithm is estimated in terms of the error of each subset. doi:10.1017/S1446181116000390

Publié le : 2017-01-01
DOI : https://doi.org/10.21914/anziamj.v58i0.11083 
@article{11083,
     title = {A study on the error of distributed algorithms for big data classification with SVM},
     journal = {ANZIAM Journal},
     volume = {58},
     year = {2017},
     doi = {10.21914/anziamj.v58i0.11083},
     language = {EN},
     url = {http://dml.mathdoc.fr/item/11083}
}

Wang, Cheng; Cao, Feilong. A study on the error of distributed algorithms for big data classification with SVM. ANZIAM Journal, Tome 58 (2017) . doi : 10.21914/anziamj.v58i0.11083. http://gdmltest.u-ga.fr/item/11083/