Communications of the ACM
C4.5: programs for machine learning
C4.5: programs for machine learning
Pattern Recognition Letters
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Document classification on neural networks using only positive examples (poster session)
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Positive and Unlabeled Examples Help Learning
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Learning from Positive and Unlabeled Examples
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
PEBL: positive example based learning for Web page classification using SVM
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Concept learning in the absence of counterexamples: an autoassociation-based approach to classification
One-class svms for document classification
The Journal of Machine Learning Research
Uniform object generation for optimizing one-class classifiers
The Journal of Machine Learning Research
Building Text Classifiers Using Positive and Unlabeled Examples
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
PEBL: Web Page Classification without Negative Examples
IEEE Transactions on Knowledge and Data Engineering
Authorship verification as a one-class classification problem
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Single-Class Classification with Mapping Convergence
Machine Learning
One-Class Classification for Spontaneous Facial Expression Analysis
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Using an Ensemble of One-Class SVM Classifiers to Harden Payload-based Anomaly Detection Systems
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
One-Class Novelty Detection for Seizure Analysis from Intracranial EEG
The Journal of Machine Learning Research
Learning to classify texts using positive and unlabeled data
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
One-class support vector machines-an application in machine fault detection and classification
Computers and Industrial Engineering
An evolutionary approach to automatic kernel construction
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
A new random forest method for one-class classification
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Open-Set classification for automated genre identification
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
A parallel genetic programming for single class classification
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Robust novelty detection in the framework of a contamination neighbourhood
International Journal of Intelligent Information and Database Systems
Robust novelty detection in the framework of a contamination neighbourhood
International Journal of Intelligent Information and Database Systems
Pattern Recognition
Computers and Electronics in Agriculture
Density weighted support vector data description
Expert Systems with Applications: An International Journal
Hybrid model of clustering and kernel autoassociator for reliable vehicle type classification
Machine Vision and Applications
Review: A review of novelty detection
Signal Processing
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The One Class Classification (OCC) problem is different from the conventional binary/multi-class classification problem in the sense that in OCC, the negative class is either not present or not properly sampled. The problem of classifying positive (or target) cases in the absence of appropriately-characterized negative cases (or outliers) has gained increasing attention in recent years. Researchers have addressed the task of OCC by using different methodologies in a variety of application domains. In this paper we formulate a taxonomy with three main categories based on the way OCC has been envisaged, implemented and applied by various researchers in different application domains. We also present a survey of current state-of-the-art OCC algorithms, their importance, applications and limitations.