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KAIS
2010
144views more  KAIS 2010»
13 years 6 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
BMCBI
2008
93views more  BMCBI 2008»
13 years 7 months ago
VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens
Background: Prediction of bacterial virulent protein sequences has implications for identification and characterization of novel virulence-associated factors, finding novel drug/v...
Aarti Garg, Dinesh Gupta
ICANNGA
2007
Springer
149views Algorithms» more  ICANNGA 2007»
14 years 1 months ago
Using Real-Valued Meta Classifiers to Integrate and Contextualize Binding Site Predictions
Currently the best algorithms for transcription factor binding site predictions are severely limited in accuracy. However, a non-linear combination of these algorithms could improv...
Mark Robinson, Offer Sharabi, Yi Sun, Rod Adams, R...
IJNSEC
2006
112views more  IJNSEC 2006»
13 years 7 months ago
An Access Control System with Time-constraint Using Support Vector Machines
Access control is an important issue in information security. It is a necessary mechanism for protecting data in a computer system. In this paper, we apply support vector machines...
Chin-Chen Chang, Iuon-Chang Lin, Chia-Te Liao
IWANN
2005
Springer
14 years 1 months ago
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...