SOTAVerified

Multi-class Classification

Multi-class classification is a type of supervised learning where the goal is to assign an input to one of three or more distinct classes. Unlike binary classification (which has only two classes), multi-class classification handles multiple labels and uses algorithms like logistic regression, decision trees, random forests, SVMs, or neural networks to predict the correct category based on the features of the input data.

Papers

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Showing 751–775 of 903 papers

TitleStatusHype
Confidence Calibration for Domain Generalization under Covariate Shift—0
Confidence Prediction for Lexicon-Free OCR—0
Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods—0
Constrained Multi-Layer Contrastive Learning for Implicit Discourse Relationship Recognition—0
Contrastive Learning for Fair Representations—0
Convergence of Uncertainty Sampling for Active Learning—0
Convergence Rates of Active Learning for Maximum Likelihood Estimation—0
Convergence rates of sub-sampled Newton methods—0
Convolutional Neural Networks in Multi-Class Classification of Medical Data—0
Correlation-based construction of neighborhood and edge features—0
Counterfactual Explanations for Predictive Business Process Monitoring—0
COV-ELM classifier: An Extreme Learning Machine based identification of COVID-19 using Chest X-Ray Images—0
CPS Attack Detection under Limited Local Information in Cyber Security: A Multi-node Multi-class Classification Ensemble Approach—0
Critical Review for One-class Classification: recent advances and the reality behind them—0
Cross-domain Recommendation via Deep Domain Adaptation—0
Revisiting Classification Perspective on Scene Text Recognition—0
Curriculum Learning for Speech Emotion Recognition from Crowdsourced Labels—0
Cut your Losses with Squentropy—0
CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks—0
Data-dependent Generalization Bounds for Multi-class Classification—0
Data-Driven Fault Diagnosis Analysis and Open-Set Classification of Time-Series Data—0
Data-driven root-cause analysis for distributed system anomalies—0
DCSVM: Fast Multi-class Classification using Support Vector Machines—0
Decentralized Online Learning with Kernels—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
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All datasetsCOVID-19 CXR DatasetCOVID chest X-rayReuters-52TII-SSRC-23Training and validation dataset of capsule vision 2024 challenge.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COVID-CXNetAccuracy (%)94.2—Unverified
#ModelMetricClaimedVerifiedStatus
1COVID-ResNetF1 score0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SVM (tficf)Macro F173.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified