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 751–800 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
Deep Attention Model for Triage of Emergency Department Patients—0
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables—0
Deep Convolutional Neural Network based Classification of Alzheimer's Disease using MRI data—0
Deep Learning Approaches for Blood Disease Diagnosis Across Hematopoietic Lineages—0
Deep Learning-based automated classification of Chinese Speech Sound Disorders—0
Deep Learning-Based Intra Mode Derivation for Versatile Video Coding—0
Deep Multi Label Classification in Affine Subspaces—0
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy—0
Deep reinforced active learning for multi-class image classification—0
Deep Sequence Models for Text Classification Tasks—0
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis—0
Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification—0
Degrees of Freedom in Deep Neural Networks—0
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification—0
Dermoscopic Image Analysis for ISIC Challenge 2018—0
Described Spatial-Temporal Video Detection—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
Detecting immune cells with label-free two-photon autofluorescence and deep learning—0
Detecting Throat Cancer from Speech Signals using Machine Learning: A Scoping Literature Review—0
Detecting Tweets Reporting Birth Defect Pregnancy Outcome Using Two-View CNN RNN Based Architecture—0
Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilities—0
Detection of Suicidal Risk on Social Media: A Hybrid Model—0
Diagnosis and Severity Assessment of Ulcerative Colitis using Self Supervised Learning—0
Diagnosis of Diabetic Retinopathy in Ethiopia: Before the Deep Learning based Automation—0
DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks—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