Integration of feature vector selection and support vector machine for classification of imbalanced data

This publication has 41 references indexed in Scilit:

• An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
  Information Sciences, 2013
• Predicting disease risks from highly imbalanced data using random forest
  BMC Medical Informatics and Decision Making, 2011
• Unsupervised feature extraction via kernel subspace techniques
  Neurocomputing, 2011
• Model selection for the LS-SVM. Application to handwriting recognition
  Pattern Recognition, 2009
• Classification of weld flaws with imbalanced class data
  Expert Systems with Applications, 2008
• KEEL: a software tool to assess evolutionary algorithms for data mining problems
  Soft Computing, 2008
• A study of the behavior of several methods for balancing machine learning training data
  ACM SIGKDD Explorations Newsletter, 2004
• Practical selection of SVM parameters and noise estimation for SVM regression
  Neural Networks, 2004
• RBF neural network center selection based on Fisher ratio class separability measure
  IEEE Transactions on Neural Networks, 2002
• Support-vector networks
  Machine Learning, 1995