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 76–100 of 903 papers

TitleStatusHype
A Fully Hyperbolic Neural Model for Hierarchical Multi-Class ClassificationCode1
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification TasksCode1
Spatio-Temporal EEG Representation Learning on Riemannian Manifold and Euclidean SpaceCode1
Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertaintyCode1
Online probabilistic label treesCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
sEMG Gesture Recognition with a Simple Model of AttentionCode1
Automated detection of COVID-19 cases using deep neural networks with X-ray imagesCode1
Null It Out: Guarding Protected Attributes by Iterative Nullspace ProjectionCode1
Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and PracticeCode1
Multi-class Gaussian Process Classification with Noisy InputsCode1
Sparse Orthogonal Variational Inference for Gaussian ProcessesCode1
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer ClassificationCode1
Efficient Set-Valued Prediction in Multi-Class ClassificationCode1
Evidential Deep Learning to Quantify Classification UncertaintyCode1
SentEval: An Evaluation Toolkit for Universal Sentence RepresentationsCode1
HDLTex: Hierarchical Deep Learning for Text ClassificationCode1
One-step and Two-step Classification for Abusive Language Detection on TwitterCode1
Learning from Complementary LabelsCode1
SOL: A Library for Scalable Online Learning AlgorithmsCode1
A Practioner's Guide to Evaluating Entity Resolution ResultsCode1
Detecting immune cells with label-free two-photon autofluorescence and deep learning—0
SHORE: A Long-term User Lifetime Value Prediction Model in Digital Games—0
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning—0
Multi-output Classification using a Cross-talk Architecture for Compound Fault Diagnosis of Motors in Partially Labeled Condition—0
Show:102550
← PrevPage 4 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