We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimension...
We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
This paper introduces an approach to sentiment analysis which uses support vector machines (SVMs) to bring together diverse sources of potentially pertinent information, including...
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...