An online AUC formulation for binary classification

DOI10.1016/j.patcog.2011.11.020zbMath1234.68342OpenAlexW2011536028WikidataQ58424106 ScholiaQ58424106MaRDI QIDQ408053

Kar-Ann Toh, Youngsung Kim, How-Lung Eng, Wei-Yun Yau, Andrew Beng Jin Teoh

Publication date: 28 March 2012

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.11.020

zbMATH Keywords

online learningbinary classificationarea under the ROC curve (AUC)receiver operating characteristics (ROC)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

ROC curves for regression

Uses Software

• Matlab
• UCI-ml
• SVM
• SGD-QN

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric analysis of fingerprint data on large data sets
• Maximizing area under ROC curve for biometric scores fusion
• Kernel affine projection algorithms
• Iterative Boolean combination of classifiers in the ROC space: an application to anomaly detection with HMMs
• Fusion of color, local spatial and global frequency information for face recognition
• ROC curve estimation and hypothesis testing: Applications to breast cancer detection
• A multinomial selection procedure for evaluating pattern recognition algorithms
• Support-vector networks
• A neural network architecture for incremental learning
• Partial AUC maximization in a linear combination of dichotomizers
• Maximizing the area under the ROC curve by pairwise feature combination
• Theoretical foundations of the potential function method in pattern recognition learning
• Problems of identification and control
• A multi-model selection framework for unknown and/or evolutive misclassification cost problems
• 10.1162/15324430260185600
• Lyapunov techniques for the exponential stability of linear difference equations with random coefficients
• A variable step size LMS algorithm
• Introduction to Stochastic Search and Optimization
• The Kernel Least-Mean-Square Algorithm
• Extended Kernel Recursive Least Squares Algorithm
• 10.1162/1532443041827916
• Online Learning with Kernels
• The Kernel Recursive Least-Squares Algorithm
• Adjustment of an Inverse Matrix Corresponding to a Change in One Element of a Given Matrix
• SOME THEOREMS IN LEAST SQUARES
• A Stochastic Approximation Method
• Global optimization
• Robust classification for imprecise environments
• The elements of statistical learning. Data mining, inference, and prediction
• The relaxed online maximum margin algorithm

This page was built for publication: An online AUC formulation for binary classification