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A Social-Spider Optimization Approach for Support Vector Machines Parameters Tuning
(Ieee, 2014-01-01)
The choice of hyper-parameters in Support Vector Machines (SVM)-based learning is a crucial task, since different values may degrade its performance, as well as can increase the computational burden. In this paper, we ...
A social-spider optimization approach for support vector machines parameters tuning
(2015-01-01)
The choice of hyper-parameters in Support Vector Machines (SVM)-based learning is a crucial task, since different values may degrade its performance, as well as can increase the computational burden. In this paper, we ...
Social-spider optimization-based artificial neural networks training and its applications for Parkinson's disease identification
(Ieee, 2014-01-01)
Evolutionary algorithms have been widely used for Artificial Neural Networks (ANN) training, being the idea to update the neurons' weights using social dynamics of living organisms in order to decrease the classification ...
Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments
(Ieee, 2014-01-01)
Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. ...
Social-Spider Optimization-based Support Vector Machines applied for energy theft detection
(Elsevier B.V., 2016-01-01)
The problem of Support Vector Machines (SVM) tuning parameters (i.e., model selection) has been paramount in the last years, mainly because of the high computational burden for SVM training step. In this paper, we address ...