An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A study of thresholding strategies for text categorization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
KBA: Kernel Boundary Alignment Considering Imbalanced Data Distribution
IEEE Transactions on Knowledge and Data Engineering
Multi-Classification by Using Tri-Class SVM
Neural Processing Letters
Dual unification of bi-class support vector machine formulations
Pattern Recognition
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
The class imbalance problem: A systematic study
Intelligent Data Analysis
An Improved Support Vector Machine for the Classification of Imbalanced Biological Datasets
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Imbalanced SVM Learning with Margin Compensation
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Evolutionary rule-based systems for imbalanced data sets
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
Classifying Remote Sensing Data with Support Vector Machines and Imbalanced Training Data
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
IEEE Transactions on Knowledge and Data Engineering
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Learning from imbalanced data in surveillance of nosocomial infection
Artificial Intelligence in Medicine
On strategies for imbalanced text classification using SVM: A comparative study
Decision Support Systems
SVMs modeling for highly imbalanced classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
An improved support vector machine with soft decision-making boundary
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Rapid and brief communication: Unified dual for bi-class SVM approaches
Pattern Recognition
FSVM-CIL: fuzzy support vector machines for class imbalance learning
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Boosting support vector machines for imbalanced data sets
Knowledge and Information Systems
Rare Class Classification by Support Vector Machine
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Borderline over-sampling for imbalanced data classification
International Journal of Knowledge Engineering and Soft Data Paradigms
Sample subset optimization for classifying imbalanced biological data
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Boosting prediction accuracy on imbalanced datasets with SVM ensembles
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
EUS SVMs: ensemble of under-sampled SVMs for data imbalance problems
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
z-SVM: an SVM for improved classification of imbalanced data
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
A novel algorithm applied to classify unbalanced data
Applied Soft Computing
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
A Note on the Bias in SVMs for Multiclassification
IEEE Transactions on Neural Networks
A study on output normalization in multiclass SVMs
Pattern Recognition Letters
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A new support vector machine, SVM, is introduced, called GSVM, which is specially designed for bi-classification problems where balanced accuracy between classes is the objective. Starting from a standard SVM, the GSVM is obtained from a low-cost post-processing strategy by modifying the initial bias. Thus, the bias for GSVM is calculated by moving the original bias in the SVM to improve the geometric mean between the true positive rate and the true negative rate. The proposed solution neither modifies the original optimization problem for SVM training, nor introduces new hyper-parameters. Experimentation carried out on a high number of databases (23) shows GSVM obtaining the desired balanced accuracy between classes. Furthermore, its performance improves well-known cost-sensitive schemes for SVM, without adding complexity or computational cost.