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 251–300 of 903 papers

TitleStatusHype
Venn Diagram Multi-label Class Interpretation of Diabetic Foot Ulcer with Color and Sharpness Enhancement—0
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression—0
UCF: Uncovering Common Features for Generalizable Deepfake DetectionCode3
T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer ClassificationCode0
Vision-based Estimation of Fatigue and Engagement in Cognitive Training SessionsCode0
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus ImagesCode0
Multi-label Node Classification On Graph-Structured DataCode1
Performance of GAN-based augmentation for deep learning COVID-19 image classificationCode0
MisRoBÆRTa: Transformers versus MisinformationCode0
1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge—0
Learning Optimal Fair Scoring Systems for Multi-Class Classification—0
KeyDetect --Detection of anomalies and user based on Keystroke Dynamics—0
A BERT-based Unsupervised Grammatical Error Correction Framework—0
Neuro-symbolic Rule Learning in Real-world Classification TasksCode0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
Automatic pain recognition from Blood Volume Pulse (BVP) signal using machine learning techniques—0
DPPMask: Masked Image Modeling with Determinantal Point Processes—0
Transformer Models for Acute Brain Dysfunction Prediction—0
Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language ModelsCode1
Machine learning tools to improve nonlinear modeling parameters of RC columns—0
Graph-based Extreme Feature Selection for Multi-class Classification Tasks—0
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations?—0
FLAG: Fast Label-Adaptive Aggregation for Multi-label Classification in Federated Learning—0
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image DetectionCode1
MVMTnet: A Multi-variate Multi-modal Transformer for Multi-class Classification of Cardiac Irregularities Using ECG Waveforms and Clinical NotesCode1
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker—0
Occupant's Behavior and Emotion Based Indoor Environment's Illumination Regulation—0
Optimal Transport for Change Detection on LiDAR Point CloudsCode0
Capsules as viewpoint learners for human pose estimation—0
Cut your Losses with Squentropy—0
1st Place Solution for PSG competition with ECCV'22 SenseHuman WorkshopCode2
Conformalized Semi-supervised Random Forest for Classification and Abnormality DetectionCode0
Classified as unknown: A novel Bayesian neural network—0
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification—0
Conformal inference is (almost) free for neural networks trained with early stoppingCode0
Increasing Fairness via Combination with Learning Guarantees—0
WDC Products: A Multi-Dimensional Entity Matching BenchmarkCode1
ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models—0
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification—0
Anomaly Detection using Ensemble Classification and Evidence Theory—0
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Query Your Model with Definitions in FrameNet: An Effective Method for Frame Semantic Role LabelingCode1
YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution DetectionCode1
Learning Disentangled Label Representations for Multi-label Classification—0
Semi-supervised binary classification with latent distance learning—0
X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications—0
Condensed Gradient BoostingCode0
A Masked Face Classification Benchmark on Low-Resolution Surveillance ImagesCode0
Unsupervised Face Recognition using Unlabeled Synthetic DataCode1
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—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
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified