Efficient computations for large least square support vector machine classifiers

A Hybrid Model Based on Support Vector Machine for Bus Travel-Time Prediction

“…Based on equality constraint, Suykens and Vandewalle [31] proposed the least square support vector machines (LS-SVM). Using the Sheman-Morrison-Woodewalle equation, Chua [32] applied SVM in large samples. However, outcome data lacked stability.…”

Model selection for the LS-SVM. Application to handwriting recognition

“…In [23], an improved algorithm also based on the conjugate gradient is developed with reducing the computational time. As other methods for training LS-SVM, we can cite the SMO technique adapted to find the LS-SVM solution and an algebraic method proposed by Chua in [9].…”

Automated Classification of Power-Quality Disturbances Using SVM and RBF Networks

“…In this case, the SVM maps the input vectors x into a high dimensional space through some nonlinear mapping (F function), where an optimal hyperplane is constructed [7], [8]. Schematic structure of the SVM network is shown in Fig.…”