Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
An Effective Machine Learning Algorithm using Momentum Scheduling
HIS '04 Proceedings of the Fourth International Conference on Hybrid Intelligent Systems
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Regularization and finding optimal solution for the classification problems are well known issue in the machine learning, but most of researches have been separately studied or considered as a same problem about these two issues. However, it is obvious that these approaches are not always possible because the evaluation of the performance in classification problems is mostly based on the data distribution and learning methods; therefore this paper suggests a new approach to simultaneously deal with finding optimal regularization parameter and solution in classification and regression problems by introducing dynamically rescheduled momentum with modified SVM in kernel space.