TY - GEN
T1 - Kernel matching reduction algorithms for classification
AU - Li, Jianwu
AU - Deng, Xiaocheng
PY - 2008
Y1 - 2008
N2 - Inspired by kernel matching pursuit (KMP) and support vector machines (SVMs), we propose a novel classification algorithm: kernel matching reduction algorithm (KMRA). This method selects all training examples to construct a kernel-based functions dictionary. Then redundant functions are removed iteratively from the dictionary, according to their weights magnitudes, which are determined by linear support vector machines (SVMs). During the reduction process, the parameters of the functions in the dictionary can be adjusted dynamically. Similarities and differences between KMRA and several other machine learning algorithms are also addressed. Experimental results show KMRA can have sparser solutions than SVMs, and can still obtain comparable classification accuracies to SVMs.
AB - Inspired by kernel matching pursuit (KMP) and support vector machines (SVMs), we propose a novel classification algorithm: kernel matching reduction algorithm (KMRA). This method selects all training examples to construct a kernel-based functions dictionary. Then redundant functions are removed iteratively from the dictionary, according to their weights magnitudes, which are determined by linear support vector machines (SVMs). During the reduction process, the parameters of the functions in the dictionary can be adjusted dynamically. Similarities and differences between KMRA and several other machine learning algorithms are also addressed. Experimental results show KMRA can have sparser solutions than SVMs, and can still obtain comparable classification accuracies to SVMs.
KW - Kernel matching pursuit
KW - Kernel matching reduction algorithms
KW - Radial basis function neural networks
KW - Support vector machines
UR - http://www.scopus.com/inward/record.url?scp=44649105231&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-79721-0_76
DO - 10.1007/978-3-540-79721-0_76
M3 - Conference contribution
AN - SCOPUS:44649105231
SN - 3540797203
SN - 9783540797203
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 564
EP - 571
BT - Rough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings
T2 - 3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008
Y2 - 17 May 2008 through 19 May 2008
ER -