Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
The nature of statistical learning theory
The nature of statistical learning theory
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Machine learning and genetic algorithms in pharmaceutical development and manufacturing processes
Decision Support Systems
Simple estimate of the width in Gaussian kernel with adaptive scaling technique
Applied Soft Computing
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In this Letter an efficient recursive update algorithm for least squares support vector machines (LSSVMs) is developed. Using the previous solution and some matrix equations, the algorithm completely avoids training the LSSVM all over again whenever new training sample is available. The gain in speed using the recursive update algorithm is illustrated on four data sets from UCI repository: the Statlog Australian credit, the Pima Indians diabetes, the Wisconsin breast cancer, and the adult income data sets.