Results 241 to 250 of about 427,183 (276)
Some of the next articles are maybe not open access.
2006
Support Vector Machines (SVMs) are a set of related methods for supervised learning, applicable to both classification and regression problems. A SVM classifiers creates a maximum-margin hyperplane that lies in a transformed input space and splits the example classes, while maximizing the distance to the nearest cleanly split examples.
openaire +2 more sources
Support Vector Machines (SVMs) are a set of related methods for supervised learning, applicable to both classification and regression problems. A SVM classifiers creates a maximum-margin hyperplane that lies in a transformed input space and splits the example classes, while maximizing the distance to the nearest cleanly split examples.
openaire +2 more sources
2001
Support vector machines are based on the theoretical learning theory developed by Vapnik [12], [17, pp. 92-129], [48], who defies the conventional belief that the optimal classification system can be developed using the optimally reduced features. In support vector machines, an n-class problem is converted into n two-class problems in which one class ...
openaire +1 more source
Support vector machines are based on the theoretical learning theory developed by Vapnik [12], [17, pp. 92-129], [48], who defies the conventional belief that the optimal classification system can be developed using the optimally reduced features. In support vector machines, an n-class problem is converted into n two-class problems in which one class ...
openaire +1 more source
Support vector machines in remote sensing: A review
ISPRS Journal of Photogrammetry and Remote Sensing, 2011Giorgos Mountrakis, Jungho Im
exaly
Financial time series forecasting using support vector machines
Neurocomputing, 2003Kyoung-Jae Kim
exaly
A wrapper method for feature selection using Support Vector Machines
Information Sciences, 2009Sebastian Maldonado, Richard Weber
exaly