On the Error-Reject Trade-Off in Biometric Verification Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Open Systems & Information Dynamics
Support Vector Machines with Embedded Reject Option
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Classification with Reject Option in Text Categorisation Systems
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Reducing the classification cost of support vector classifiers through an ROC-based reject rule
Pattern Analysis & Applications
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Covering numbers for support vector machines
IEEE Transactions on Information Theory
Capacity of reproducing kernel spaces in learning theory
IEEE Transactions on Information Theory
Learning Nondeterministic Classifiers
The Journal of Machine Learning Research
Classification Methods with Reject Option Based on Convex Risk Minimization
The Journal of Machine Learning Research
Adapting cost-sensitive learning for reject option
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Predicting partial orders: ranking with abstention
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Computational Statistics & Data Analysis
Viability of an alarm predictor for coffee rust disease using interval regression
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
A family of measures for best top-n class-selective decision rules
Pattern Recognition
Shaping the error-reject curve of error correcting output coding systems
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Learning data structure from classes: A case study applied to population genetics
Information Sciences: an International Journal
Active learning via perfect selective classification
The Journal of Machine Learning Research
Design of reject rules for ECOC classification systems
Pattern Recognition
A survey of multiple classifier systems as hybrid systems
Information Fusion
A unified view of class-selection with probabilistic classifiers
Pattern Recognition
Robust ordinal regression in preference learning and ranking
Machine Learning
The data replication method for the classification with reject option
AI Communications
Hi-index | 0.00 |
We consider the problem of binary classification where the classifier can, for a particular cost, choose not to classify an observation. Just as in the conventional classification problem, minimization of the sample average of the cost is a difficult optimization problem. As an alternative, we propose the optimization of a certain convex loss function φ, analogous to the hinge loss used in support vector machines (SVMs). Its convexity ensures that the sample average of this surrogate loss can be efficiently minimized. We study its statistical properties. We show that minimizing the expected surrogate lossthe φ-riskalso minimizes the risk. We also study the rate at which the φ-risk approaches its minimum value. We show that fast rates are possible when the conditional probability P(Y=1|X) is unlikely to be close to certain critical values.