The algebraic eigenvalue problem
The algebraic eigenvalue problem
The nature of statistical learning theory
The nature of statistical learning theory
The symmetric eigenvalue problem
The symmetric eigenvalue problem
Making large-scale support vector machine learning practical
Advances in kernel methods
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Support vector machines: hype or hallelujah?
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Support Vector Machine for Regression and Applications to Financial Forecasting
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Joint time-frequency-space classification of EEG in a brain-computer interface application
EURASIP Journal on Applied Signal Processing
A Supervised Learning Technique and Its Applications to Computational Biology
Computational Intelligence Methods for Bioinformatics and Biostatistics
Proximal support vector machine using local information
Neurocomputing
A parallel classification and feature reduction method for biomedical applications
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Multi-weight vector projection support vector machines
Pattern Recognition Letters
Localized twin SVM via convex minimization
Neurocomputing
Distance difference and linear programming nonparallel plane classifier
Expert Systems with Applications: An International Journal
Generalized eigenvalue proximal support vector regressor
Expert Systems with Applications: An International Journal
Artificial Intelligence in Medicine
Supervised classification methods for mining cell differences as depicted by Raman spectroscopy
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
Fuzzy regularized generalized eigenvalue classifier with a novel membership function
Information Sciences: an International Journal
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Binary classification refers to supervised techniques that split a set of points in two classes, with respect to a training set of points whose membership is known for each class. Binary classification plays a central role in the solution of many scientific, financial, engineering, medical and biological problems. Many methods with good classification accuracy are currently available. This work shows how a binary classification problem can be expressed in terms of a generalized eigenvalue problem. A new regularization technique is proposed, which gives results that are comparable to other techniques in use, in terms of classification accuracy. The advantage of this method relies in its lower computational complexity with respect to the existing techniques based on generalized eigenvalue problems. Finally, the method is compared with other methods using benchmark data sets.