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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 151–200 of 227 papers

TitleStatusHype
Identification of Abnormal States in Videos of Ants Undergoing Social Phase ChangeCode0
STEP-GAN: A Step-by-Step Training for Multi Generator GANs with application to Cyber Security in Power Systems—0
_p-Norm Multiple Kernel One-Class Fisher Null-Space—0
Unsupervised Transfer Learning for Anomaly Detection: Application to Complementary Operating Condition Transfer—0
Quantum One-class Classification With a Distance-based ClassifierCode0
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant NetworkCode0
G2D: Generate to Detect Anomaly—0
Use of in-the-wild images for anomaly detection in face anti-spoofing—0
Applying support vector data description for fraud detection—0
Policy Entropy for Out-of-Distribution Classification—0
Detecting Adversarial Examples for Speech Recognition via Uncertainty QuantificationCode0
Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification—0
Towards Anomaly Detection in Dashcam Videos—0
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis—0
Ellipsoidal Subspace Support Vector Data DescriptionCode0
Meta-SVDD: Probabilistic Meta-Learning for One-Class Classification in Cancer Histology Images—0
DROCC: Deep Robust One-Class Classification—0
Boosting rare benthic macroinvertebrates taxa identification with one-class classification—0
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification—0
Comparison of Statistical and Machine Learning Techniques for Physical Layer Authentication—0
Unsupervised Learning of the Set of Local Maxima—0
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning—0
Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders—0
One-Class Classification by Ensembles of Regression models -- a detailed studyCode0
NFAD: Fixing anomaly detection using normalizing flowsCode0
Metre as a stylometric feature in Latin hexameter poetryCode0
Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data—0
Statistical and Machine Learning-based Decision Techniques for Physical Layer Authentication—0
Domain Adaptation for One-Class Classification: Monitoring the Health of Critical Systems Under Limited Information—0
Contextual One-Class Classification in Data Streams—0
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on TextCode0
Domain Adaptive Attention Learning for Unsupervised Person Re-Identification—0
Multi-Task Kernel Null-Space for One-Class Classification—0
A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing—0
End-to-End Adversarial Learning for Intrusion Detection in Computer Networks—0
Multimodal Subspace Support Vector Data DescriptionCode0
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
Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)—0
Active Authentication using an Autoencoder regularized CNN-based One-Class ClassifierCode0
Robust One-Class Kernel Spectral Regression—0
Deep One-Class Classification Using Intra-Class Splitting—0
Generalizing Fingerprint Spoof Detector: Learning a One-Class Classifier—0
Active Learning for One-Class Classification Using Two One-Class Classifiers—0
One-Class Feature Learning Using Intra-Class Splitting—0
OCLEP+: One-class Anomaly and Intrusion Detection Using Minimal Length of Emerging Patterns—0
Feature Learning for Fault Detection in High-Dimensional Condition-Monitoring SignalsCode0
Deep One-Class ClassificationCode0
CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition—0
Localized Multiple Kernel Learning for Anomaly Detection: One-class ClassificationCode0
Multi-layer Kernel Ridge Regression for One-class Classification—0
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