Sciweavers

304 search results - page 12 / 61
» How good are support vector machines
Sort
View
BIOCOMP
2006
13 years 9 months ago
Support Vector Machines for Predicting microRNA Hairpins
- microRNAs (miRNAs) are 20-22 nt noncoding RNAs which are rapidly emerging as crucial regulators of gene expression in plants and animals. Identification of the hairpins which yie...
Karol Szafranski, Molly Megraw, Martin Reczko, Art...
NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
CVPR
2009
IEEE
1351views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Support Vector Machines in Face Recognition with Occlusions
Support Vector Machines (SVM) are one of the most useful techniques in classification problems. One clear example is face recognition. However, SVM cannot be applied when the fe...
Aleix M. Martínez, Hongjun Jia
ESWA
2006
122views more  ESWA 2006»
13 years 7 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
TMI
2010
172views more  TMI 2010»
13 years 6 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...