TY - GEN
T1 - Application of the cross-entropy method to dual Lagrange support vector machine
AU - Santosa, Budi
PY - 2009
Y1 - 2009
N2 - In this paper, cross entropy method is used for solving dual Lagrange support vector machine (SVM). Cross entropy (CE) method is a new practical approach which is widely used in some applications such as combinatorial optimization, learning algorithm and simulation. Our approach refers to Kernel Adatron which is solving dual Lagrange SVM using gradient ascent method. Hereby, the cross entropy method is applied to solve dual Lagrange SVM optimization problem to find the optimal or at least near optimal Lagrange multipliers as a solution. As known, the standard SVM with quadratic programming solver suffers from high computational time. Some real world datasets are used to test the algorithms and compare to the existing approach in terms of computation time and accuracy. Our approach is fast and produce good results in terms of generalization error.
AB - In this paper, cross entropy method is used for solving dual Lagrange support vector machine (SVM). Cross entropy (CE) method is a new practical approach which is widely used in some applications such as combinatorial optimization, learning algorithm and simulation. Our approach refers to Kernel Adatron which is solving dual Lagrange SVM using gradient ascent method. Hereby, the cross entropy method is applied to solve dual Lagrange SVM optimization problem to find the optimal or at least near optimal Lagrange multipliers as a solution. As known, the standard SVM with quadratic programming solver suffers from high computational time. Some real world datasets are used to test the algorithms and compare to the existing approach in terms of computation time and accuracy. Our approach is fast and produce good results in terms of generalization error.
KW - Computation time
KW - Cross entropy
KW - Generalization error
KW - Kernel adatron
KW - Lagrange
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=70350342518&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-03348-3_61
DO - 10.1007/978-3-642-03348-3_61
M3 - Conference contribution
AN - SCOPUS:70350342518
SN - 3642033474
SN - 9783642033476
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 595
EP - 602
BT - Advanced Data Mining and Applications - 5th International Conference, ADMA 2009, Proceedings
T2 - 5th International Conference on Advanced Data Mining and Applications, ADMA 2009
Y2 - 17 August 2009 through 19 August 2009
ER -