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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

Showing 151175 of 227 papers

TitleStatusHype
Few-Shot One-Class Classification via Meta-LearningCode1
Explainable Deep One-Class ClassificationCode1
G2D: Generate to Detect Anomaly0
Use of in-the-wild images for anomaly detection in face anti-spoofing0
Applying support vector data description for fraud detection0
Policy Entropy for Out-of-Distribution Classification0
Detecting Adversarial Examples for Speech Recognition via Uncertainty QuantificationCode0
Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification0
Towards Anomaly Detection in Dashcam Videos0
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionCode1
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis0
Ellipsoidal Subspace Support Vector Data DescriptionCode0
Meta-SVDD: Probabilistic Meta-Learning for One-Class Classification in Cancer Histology Images0
DROCC: Deep Robust One-Class Classification0
One-Class Graph Neural Networks for Anomaly Detection in Attributed NetworksCode1
Boosting rare benthic macroinvertebrates taxa identification with one-class classification0
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification0
Comparison of Statistical and Machine Learning Techniques for Physical Layer Authentication0
Unsupervised Learning of the Set of Local Maxima0
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning0
Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders0
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 data0
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