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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 903 papers

TitleStatusHype
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
A Bayesian Approach for Accurate Classification-Based Aggregates—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—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
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—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
Classifying Lexical-semantic Relationships by Exploiting Sense/Concept Representations—0
Data-driven root-cause analysis for distributed system anomalies—0
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference—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
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning—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
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1COVID-ResNetF1 score0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SVM (tficf)Macro F173.9—Unverified
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1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified