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» Hybrid Kernel Machine Ensemble for Imbalanced Data Sets
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ICPR
2006
IEEE
14 years 5 months ago
Hybrid Kernel Machine Ensemble for Imbalanced Data Sets
A two-class imbalanced data problem (IDP) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. Though a discriminative...
Kap Luk Chan, Peng Li, Wen Fang
KAIS
2010
144views more  KAIS 2010»
13 years 3 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
FSKD
2008
Springer
174views Fuzzy Logic» more  FSKD 2008»
13 years 5 months ago
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
Peng Li, Pei-Li Qiao, Yuan-Chao Liu
GCB
2003
Springer
164views Biometrics» more  GCB 2003»
13 years 10 months ago
Integrative machine learning approach for multi-class SCOP protein fold classification
: Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP ...
Aik Choon Tan, David Gilbert, Yves Deville
CSL
2006
Springer
13 years 4 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...