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 201–250 of 903 papers

TitleStatusHype
Looking back at Labels: A Class based Domain Adaptation TechniqueCode0
Lovasz Convolutional NetworksCode0
Achieving Equalized Odds by Resampling Sensitive AttributesCode0
Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information NetworksCode0
MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image DeformationsCode0
MisRoBÆRTa: Transformers versus MisinformationCode0
Fuzzy granular approximation classifierCode0
InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised ClassificationCode0
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited tripletsCode0
Attention-based Context Aggregation Network for Monocular Depth EstimationCode0
Federated Learning with Only Positive LabelsCode0
Financial Data Analysis with Robust Federated Logistic RegressionCode0
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-RaysCode0
Extrapolating Expected Accuracies for Large Multi-Class ProblemsCode0
Neural Collapse in Multi-label Learning with Pick-all-label LossCode0
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian ManifoldCode0
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and AdaptivityCode0
Neuro-Argumentative Learning with Case-Based ReasoningCode0
Non-Parametric Calibration for ClassificationCode0
Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance PropagationCode0
Active Learning from Positive and Unlabeled DataCode0
Exponentially Convergent Algorithms for Supervised Matrix FactorizationCode0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing AccuracyCode0
Deep attention-based classification network for robust depth predictionCode0
Calibration tests in multi-class classification: A unifying frameworkCode0
Explainable AI for Comparative Analysis of Intrusion Detection ModelsCode0
Deep brain state classification of MEG dataCode0
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence RatesCode0
Calibration tests beyond classificationCode0
Calibrated simplex-mapping classificationCode0
Predicting delays in Indian lower courts using AutoML and Decision ForestsCode0
Primal-Dual Block Frank-WolfeCode0
Deep localization of protein structures in fluorescence microscopy imagesCode0
Analysis of French Phonetic Idiosyncrasies for Accent RecognitionCode0
Evaluating approaches for supervised semantic labelingCode0
pSVM: Soft-margin SVMs with p-norm Hinge LossCode0
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class ClassificationCode0
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case StudyCode0
Safe reinforcement learning in uncertain contextsCode0
Scalable Gaussian Process Classification with Additive Noise for Various LikelihoodsCode0
Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and MethodCode0
AutoMSC: Automatic Assignment of Mathematics Subject Classification LabelsCode0
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear LossCode0
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry BenchmarkingCode0
Breast Tumor Classification Using EfficientNet Deep Learning ModelCode0
Enhanced Network Embedding with Text InformationCode0
Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label CorrelationsCode0
Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class ClassificationCode0
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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