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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 761–770 of 903 papers

Title	Date	Tasks	Status	Hype
Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks	Apr 15, 2018	ClusteringMulti-class Classification	CodeCode Available	0
A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography	Apr 12, 2018	ClassificationGeneral Classification	—Unverified	0
Multi-level Activation for Segmentation of Hierarchically-nested Classes	Apr 5, 2018	Image SegmentationMulti-class Classification	—Unverified	0
The Resistance to Label Noise in K-NN and DNN Depends on its Concentration	Mar 30, 2018	General ClassificationMulti-class Classification	—Unverified	0
Deep Attention Model for Triage of Emergency Department Patients	Mar 28, 2018	Binary ClassificationDecision Making	—Unverified	0
Model-Agnostic Private Learning via Stability	Mar 14, 2018	Binary ClassificationClassification	—Unverified	0
SentEval: An Evaluation Toolkit for Universal Sentence Representations	Mar 14, 2018	General ClassificationMulti-class Classification	CodeCode Available	1
Dimension-Robust MCMC in Bayesian Inverse Problems	Mar 9, 2018	Active LearningEfficient Exploration	—Unverified	0
Cross-domain Recommendation via Deep Domain Adaptation	Mar 8, 2018	Collaborative FilteringDenoising	—Unverified	0
Cognitive Radar Antenna Selection via Deep Learning	Feb 27, 2018	Deep LearningGeneral Classification	—Unverified	0

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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