Making large-scale support vector machine learning practical
Advances in kernel methods
Robust Classification for Imprecise Environments
Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Optimising area under the ROC curve using gradient descent
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Validating a Biometric Authentication System: Sample Size Requirements
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Maximizing the area under the ROC curve by pairwise feature combination
Pattern Recognition
Between Classification-Error Approximation and Weighted Least-Squares Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Journal of Machine Learning Research
Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximizing area under ROC curve for biometric scores fusion
Pattern Recognition
Partial AUC maximization in a linear combination of dichotomizers
Pattern Recognition
Enhanced fisher discriminant criterion for image recognition
Pattern Recognition
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
Hyperdisk based large margin classifier
Pattern Recognition
Three-fold structured classifier design based on matrix pattern
Pattern Recognition
A new framework for optimal classifier design
Pattern Recognition
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The structural resemblance among several existing classifiers has motivated us to investigate their underlying relationships. By exploring into the mapping solutions of these classifiers, we found that they can be linked by simple feature data scaling. In other words, the key to these relationships lies upon how the replica of feature data are being scaled. This finding leads us directly to an exploration of novel classifiers beyond existing settings. Based on an extensive empirical evaluation, we show that the proposed formulation facilitates a tuning capability beyond existing settings for classifier generalization.