Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
AdaCost: Misclassification Cost-Sensitive Boosting
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
A Comparative Study of Cost-Sensitive Boosting Algorithms
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Machine Learning for Sequential Data: A Review
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Report Generation and Data Mining in the Domain of Thoracic Surgery
Journal of Medical Systems
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active learning for class imbalance problem
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Cost-sensitive boosting for classification of imbalanced data
Pattern Recognition
Development of Two-Stage SVM-RFE Gene Selection Strategy for Microarray Expression Data Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Learning on the border: active learning in imbalanced data classification
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Support Vector Machines
IEEE Transactions on Knowledge and Data Engineering
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Granular support vector machines with association rules mining for protein homology prediction
Artificial Intelligence in Medicine
SVMs modeling for highly imbalanced classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Pattern classification with missing data: a review
Neural Computing and Applications - Special Issue - KES2008
Implementation and integration of algorithms into the KEEL data-mining software tool
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Boosting support vector machines for imbalanced data sets
Knowledge and Information Systems
Borderline-SMOTE: a new over-sampling method in imbalanced data sets learning
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Artificial Intelligence in Medicine
A novel algorithm applied to classify unbalanced data
Applied Soft Computing
IEEE Transactions on Neural Networks
Extracting Rules From Neural Networks as Decision Diagrams
IEEE Transactions on Neural Networks - Part 2
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In this paper, we present boosted SVM dedicated to solve imbalanced data problems. Proposed solution combines the benefits of using ensemble classifiers for uneven data together with cost-sensitive support vectors machines. Further, we present oracle-based approach for extracting decision rules from the boosted SVM. In the next step we examine the quality of the proposed method by comparing the performance with other algorithms which deal with imbalanced data. Finally, boosted SVM is used for medical application of predicting post-operative life expectancy in the lung cancer patients.