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 801–825 of 903 papers

TitleStatusHype
Distance Guided Generative Adversarial Network for Explainable Binary ClassificationsCode0
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networksCode0
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text ClassificationCode0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
Multi-Class Abnormality Classification in Video Capsule Endoscopy Using Deep LearningCode0
Diagnosis of COVID-19 using chest X-ray images based on modified DarkCovidNet modelCode0
HemaGraph: Breaking Barriers in Hematologic Single Cell Classification with Graph AttentionCode0
Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion ImagesCode0
Source detection via multi-label classificationCode0
Auto deep learning for bioacoustic signalsCode0
Application of SsVGMM to medical data-classification with novelty detectionCode0
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set ClassificationCode0
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence RatesCode0
Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and MethodCode0
Pairwise Margin Maximization for Deep Neural NetworksCode0
Multi-class Classification with Fuzzy-feature Observations: Theory and AlgorithmsCode0
Multi-class Classification without Multi-class LabelsCode0
HSD Shared Task in VLSP Campaign 2019:Hate Speech Detection for Social GoodCode0
Beyond Adult and COMPAS: Fairness in Multi-Class PredictionCode0
Deep N-ary Error Correcting Output CodesCode0
Competing Ratio Loss for Discriminative Multi-class Image ClassificationCode0
A matter of attitude: Focusing on positive and active gradients to boost saliency mapsCode0
Imbalance Learning for Variable Star ClassificationCode0
Safe reinforcement learning in uncertain contextsCode0
Spatial encoding of BOLD fMRI time series for categorizing static images across visual datasets: A pilot study on human visionCode0
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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