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 876–900 of 903 papers

TitleStatusHype
Semi-Supervised Learning with Scarce AnnotationsCode0
Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional NetworksCode0
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep ClassifiersCode0
Word Embedding Dimension Reduction via Weakly-Supervised Feature SelectionCode0
Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing LabelsCode0
COVID-ResNet: A Deep Learning Framework for Screening of COVID19 from RadiographsCode0
Proximal Mean Field Learning in Shallow Neural NetworksCode0
Calibration tests in multi-class classification: A unifying frameworkCode0
NearbyPatchCL: Leveraging Nearby Patches for Self-Supervised Patch-Level Multi-Class Classification in Whole-Slide ImagesCode0
Network Representation Learning with Rich Text InformationCode0
pSVM: Soft-margin SVMs with p-norm Hinge LossCode0
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class ClassificationCode0
Neural Collapse in Multi-label Learning with Pick-all-label LossCode0
Learning by Minimizing the Sum of Ranked RangeCode0
Learning curves for the multi-class teacher-student perceptronCode0
Concise Explanations of Neural Networks using Adversarial TrainingCode0
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian ManifoldCode0
Consistent Structured Prediction with Max-Min Margin Markov NetworksCode0
Learning from Concealed LabelsCode0
Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk RegularizationCode0
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensionsCode0
Neural CRNs: A Natural Implementation of Learning in Chemical Reaction NetworksCode0
Sum of Ranked Range Loss for Supervised LearningCode0
A Topological Data Analysis Based ClassifierCode0
Neuro-Argumentative Learning with Case-Based ReasoningCode0
Show:102550
← PrevPage 36 of 37Next →
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