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 401–425 of 903 papers

TitleStatusHype
Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rays—0
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and AdaptivityCode0
The SAMME.C2 algorithm for severely imbalanced multi-class classification—0
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class AnnealingCode0
Contrastive Learning for Fair Representations—0
Flat and Nested Negation and Uncertainty Detection with PubMed BERT—0
Logically at Factify 2022: Multimodal Fact Verification—0
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning ModelsCode0
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep ClassifiersCode0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT—0
Neural-based Tamil Grammar Error Detection—0
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions—0
On the Value of Interaction and Function Approximation in Imitation Learning—0
A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection—0
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding—0
Event-Event Relation Extraction using Probabilistic Box Embedding—0
Margin-Independent Online Multiclass Learning via Convex Geometry—0
On Efficient Uncertainty Estimation for Resource-Constrained Mobile Applications—0
Critical Sentence Identification in Legal Cases Using Multi-Class Classification—0
A Topological Data Analysis Based ClassifierCode0
Neyman-Pearson Multi-class Classification via Cost-sensitive Learning—0
Sexism Identification in Tweets and Gabs using Deep Neural Networks—0
Co-attention network with label embedding for text classificationCode1
On the Effectiveness of Interpretable Feedforward Neural Network—0
TorchXRayVision: A library of chest X-ray datasets and modelsCode2
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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
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1SVM (tficf)Macro F173.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified