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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 151–175 of 227 papers

TitleStatusHype
Use of in-the-wild images for anomaly detection in face anti-spoofing—0
usfAD Based Effective Unknown Attack Detection Focused IDS Framework—0
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach—0
OCKELM+: Kernel Extreme Learning Machine based One-class Classification using Privileged Information (or KOC+: Kernel Ridge Regression or Least Square SVM with zero bias based One-class Classification using Privileged Information)—0
Wooden Sleeper Deterioration Detection for Rural Railway Prognostics Using Unsupervised Deeper FCDDs—0
A Perceptron-based Fine Approximation Technique for Linear Separation—0
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
Active anomaly detection based on deep one-class classification—0
Active Learning for One-Class Classification Using Two One-Class Classifiers—0
Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation—0
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
A Joint Representation Learning and Feature Modeling Approach for One-class Recognition—0
AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays—0
A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing—0
An ensemble of Density based Geometric One-Class Classifier and Genetic Algorithm—0
An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination—0
Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach—0
Anomaly detection with semi-supervised classification based on risk estimators—0
An Upper Bound for the Distribution Overlap Index and Its Applications—0
A One class Classifier based Framework using SVDD : Application to an Imbalanced Geological Dataset—0
A One-Class Classification Decision Tree Based on Kernel Density Estimation—0
Applying support vector data description for fraud detection—0
A Unifying Review of Deep and Shallow Anomaly Detection—0
Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields—0
Average Localised Proximity: A new data descriptor with good default one-class classification performance—0
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