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 401–410 of 903 papers

Title	Date	Tasks	Status
Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rays	Jan 16, 2022	ClassificationMulti-class Classification	—Unverified
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity	Dec 30, 2021	Classification ConsistencyMulti-class Classification	CodeCode Available
The SAMME.C2 algorithm for severely imbalanced multi-class classification	Dec 30, 2021	ClassificationMulti-class Classification	—Unverified
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing	Dec 27, 2021	Active LearningDiversity	CodeCode Available
Contrastive Learning for Fair Representations	Dec 17, 2021	AttributeClassification	—Unverified
Flat and Nested Negation and Uncertainty Detection with PubMed BERT	Dec 17, 2021	Multi-class ClassificationNegation	—Unverified
Logically at Factify 2022: Multimodal Fact Verification	Dec 16, 2021	BenchmarkingFact Checking	—Unverified
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models	Dec 7, 2021	Dimensionality ReductionMulti-class Classification	CodeCode Available
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers	Dec 4, 2021	ClassificationMulti-class Classification	CodeCode Available
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT	Dec 1, 2021	Hate Speech DetectionMulti-class Classification	—Unverified

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All datasets COVID-19 CXR Dataset COVID chest X-ray Reuters-52 TII-SSRC-23 Training and validation dataset of capsule vision 2024 challenge.

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	COVID-CXNet	Accuracy (%)	94.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	COVID-ResNet	F1 score	0.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SVM (tficf)	Macro F1	73.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Extra Trees	F1-Score	93.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multi-Model Ensemble	Mean AUC	0.99	—	Unverified