LS-SVMlab

From MaRDI portal
Software:19399



swMATH7367MaRDI QIDQ19399


No author found.





Related Items (25)

Asymmetric least squares support vector machine classifiersAsymmetric \(\nu\)-tube support vector regressionApplication of machine learning techniques for supply chain demand forecastingAPPLICATION OF S-TRANSFORM FOR AUTOMATED DETECTION OF VIGILANCE LEVEL USING EEG SIGNALSIndefinite kernels in least squares support vector machines and principal component analysisIdentification of S1 and S2 heart sound patterns based on fractal theory and shape contextLS-SVM Regression for Structural Damage Diagnosis Using the Iterated Improved Reduction SystemStructural damage diagnosis using incomplete static responses and LS-SVMA novel auto-regressive fractionally integrated moving average–least-squares support vector machine model for electricity spot prices predictionA kernel-based framework to tensorial data analysisLong-term time series prediction using OP-ELMA novel sparse least squares support vector machinesEfficient model selection for sparse least-square SVMsUnnamed ItemLearning with tensors: a framework based on convex optimization and spectral regularizationA new feature constituting approach to detection of vocal fold pathologyUsage of artificial intelligence methods in free flowing gated closed conduits for estimation of oxygen transfer efficiencyA WAVELET SUPPORT VECTOR MACHINE COUPLED METHOD FOR TIME SERIES PREDICTIONLS-SVM model based nonlinear predictive control for MCFC systemA modified multi-gene genetic programming approach for modelling true stress of dynamic strain aging regime of austenitic stainless steel 304Automotive engine idle speed control optimization using least squares support vector machine and genetic algorithmNonparallel plane proximal classifierApplying least squares support vector machines to mean-variance portfolio analysisSparse hierarchical regression with polynomialsNewton's method for nonparallel plane proximal classifier with unity norm hyperplanes


This page was built for software: LS-SVMlab