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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 126–150 of 227 papers

TitleStatusHype
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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