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» Less is More: Active Learning with Support Vector Machines
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BMCBI
2007
139views more  BMCBI 2007»
13 years 5 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
PKDD
2010
Springer
152views Data Mining» more  PKDD 2010»
13 years 3 months ago
Online Knowledge-Based Support Vector Machines
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
13 years 11 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
14 years 1 days ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 5 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher