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 601–625 of 903 papers

TitleStatusHype
sEMG Gesture Recognition with a Simple Model of AttentionCode1
On the Equivalence between Online and Private Learnability beyond Binary Classification—0
Minimizing Supervision in Multi-label Categorization—0
A Framework for Behavioral Biometric Authentication using Deep Metric Learning on Mobile Devices—0
AutoMSC: Automatic Assignment of Mathematics Subject Classification LabelsCode0
On Using Transfer Learning For Plant Disease Detection—0
Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification—0
Automated detection of COVID-19 cases using deep neural networks with X-ray imagesCode1
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networksCode0
Federated Learning with Only Positive LabelsCode0
Null It Out: Guarding Protected Attributes by Iterative Nullspace ProjectionCode1
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables—0
COVID-ResNet: A Deep Learning Framework for Screening of COVID19 from RadiographsCode0
Adversarial Multi-Binary Neural Network for Multi-class Classification—0
Multi-Class classification of vulnerabilities in Smart Contracts using AWD-LSTM, with pre-trained encoder inspired from natural language processing—0
Diagnosis of Diabetic Retinopathy in Ethiopia: Before the Deep Learning based Automation—0
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift—0
On the Learning Property of Logistic and Softmax Losses for Deep Neural NetworksCode0
Imbalance Learning for Variable Star ClassificationCode0
Comparison of Multi-Class and Binary Classification Machine Learning Models in Identifying Strong Gravitational Lenses—0
On the generalization of bayesian deep nets for multi-class classification—0
Optimistic bounds for multi-output prediction—0
Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and PracticeCode1
The Utility of General Domain Transfer Learning for Medical Language Tasks—0
Multi-Class Classification from Noisy-Similarity-Labeled Data—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