A subregion division based multi-objective evolutionary algorithm for SVM training set selection
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.02.028
Abstract: Abstract Support vector machine (SVM) is a popular machine learning method with a solid theoretical foundation, and has shown promising performance on different classification problems. However, it suffers from an expensive training cost, which makes… read more here.
Keywords: set selection; training set; subregion; training ... See more keywords
Adaptive Kernel Value Caching for SVM Training
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2944562
Abstract: Support vector machines (SVMs) can solve structured multioutput learning problems such as multilabel classification, multiclass classification, and vector regression. SVM training is expensive, especially for large and high-dimensional data sets. The bottleneck of the SVM… read more here.
Keywords: svm training; kernel value; training; caching strategy ... See more keywords