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» Increasing Efficiency of SVM by Adaptively Penalizing Outlie...
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EMMCVPR
2005
Springer
13 years 10 months ago
Increasing Efficiency of SVM by Adaptively Penalizing Outliers
In this paper, a novel training method is proposed to increase the classification efficiency of support vector machine (SVM). The efficiency of the SVM is determined by the number ...
Yiqiang Zhan, Dinggang Shen
PR
2006
111views more  PR 2006»
13 years 4 months ago
An adaptive error penalization method for training an efficient and generalized SVM
A novel training method has been proposed for increasing efficiency and generalization of support vector machine (SVM). The efficiency of SVM in classification is directly determi...
Yiqiang Zhan, Dinggang Shen
ECAI
2010
Springer
13 years 5 months ago
Mining Outliers with Adaptive Cutoff Update and Space Utilization (RACAS)
Recently the efficiency of an outlier detection algorithm ORCA was improved by RCS (Randomization with faster Cutoff update and Space utilization after pruning), which changes the ...
Chi-Cheong Szeto, Edward Hung
ECCV
2008
Springer
14 years 6 months ago
A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
The Random Sample Consensus (RANSAC) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction o...
Rahul Raguram, Jan-Michael Frahm, Marc Pollefeys
BMCBI
2006
126views more  BMCBI 2006»
13 years 4 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo