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One-Class Classification

One-class classification (OCC) algorithms serve a crucial role in scenarios where the negative class is either absent, poorly sampled, or not well defined. This unique situation presents a challenge for building effective classifiers, as they must delineate the class boundary solely based on knowledge of the positive class. OCC has found application in various research domains, including outlier/novelty detection and concept learning.

In the context of anomaly detection, OCC models are trained exclusively on "normal" data and are subsequently tasked with identifying anomalous patterns during inference.

A one-class classifier aims at capturing characteristics of training instances, in order to be able to distinguish between them and potential outliers to appear.

— Page 139, Learning from Imbalanced Data Sets, 2018.

Papers

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Showing 101–150 of 227 papers

TitleStatusHype
Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection—0
Learning The Likelihood Test With One-Class Classifiers for Physical Layer Authentication—0
A One-Class Classification method based on Expanded Non-Convex HullsCode0
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly DetectionCode0
[Reproducibility Report] Explainable Deep One-Class Classification—0
Generalized Reference Kernel for One-class ClassificationCode0
OCFormer: One-Class Transformer Network for Image Classification—0
"Flux+Mutability": A Conditional Generative Approach to One-Class Classification and Anomaly Detection—0
Early Myocardial Infarction Detection with One-Class Classification over Multi-view Echocardiography—0
Multi-class versus One-class classifier in spontaneous speech analysis oriented to Alzheimer Disease diagnosis—0
_p Slack Norm Support Vector Data Description—0
Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled DataCode0
Generative Cooperative Learning for Unsupervised Video Anomaly Detection—0
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
Mobile authentication of copy detection patterns—0
Towards Targeted Change Detection with Heterogeneous Remote Sensing Images for Forest Mortality Mapping—0
Data refinement for fully unsupervised visual inspection using pre-trained networks—0
On The Effectiveness of One-Class Support Vector Machine in Different Defect Prediction Scenarios—0
SAFE-OCC: A Novelty Detection Framework for Convolutional Neural Network Sensors and its Application in Process Control—0
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection—0
Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images—0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Conical Classification For Efficient One-Class Topic Determination—0
Conical Classification For Computationally Efficient One-Class Topic Determination—0
Impact of Channel Variation on One-Class Learning for Spoof DetectionCode0
Deep Inverse Reinforcement Learning via Adversarial One-Class Classification—0
Unsupervised Artifact Detection for Whole Slide Images of Prostate Biopsies—0
Conceptron: a probabilistic deep one-class classification method—0
FROB: Few-shot ROBust Model for Classification with Out-of-Distribution Detection—0
One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set Classification—0
One-Class Classification for Wafer Map using Adversarial Autoencoder with DSVDD Prior—0
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection—0
Deep Visual Anomaly detection with Negative Learning—0
DOC3-Deep One Class Classification using Contradictions—0
Graph-Embedded Subspace Support Vector Data DescriptionCode0
Multi-view Deep One-class Classification: A Systematic ExplorationCode0
Federated Learning-based Active Authentication on Mobile Devices—0
One-class Autoencoder Approach for Optimal Electrode Set-up Identification in Wearable EEG Event Monitoring—0
Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection—0
Optimised one-class classification performance—0
Average Localised Proximity: A new data descriptor with good default one-class classification performance—0
A Joint Representation Learning and Feature Modeling Approach for One-class Recognition—0
One-Class Classification: A Survey—0
One-class Classification Robust to Geometric Transformation—0
Towards Fair Deep Anomaly Detection—0
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network—0
FROCC: Fast Random projection-based One-Class Classification—0
Minimum Variance Embedded Auto-associative Kernel Extreme Learning Machine for One-class Classification—0
An ensemble of Density based Geometric One-Class Classifier and Genetic Algorithm—0
A Unifying Review of Deep and Shallow Anomaly Detection—0
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