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 176–200 of 903 papers

Title	Date	Tasks	Status	Score
Food Classification with Convolutional Neural Networks and Multi-Class Linear Discernment Analysis	Dec 6, 2020	ClassificationGeneral Classification	CodeCode Available	5
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-Rays	Jun 21, 2024	Multi-class ClassificationPneumonia Detection	CodeCode Available	5
HSD Shared Task in VLSP Campaign 2019:Hate Speech Detection for Social Good	Jul 13, 2020	General ClassificationHate Speech Detection	CodeCode Available	5
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification	Sep 26, 2019	General Classificationgraph construction	CodeCode Available	5
Improving Bias Mitigation through Bias Experts in Natural Language Understanding	Dec 6, 2023	Binary ClassificationMulti-class Classification	CodeCode Available	5
Extrapolating Expected Accuracies for Large Multi-Class Problems	Dec 27, 2017	General ClassificationMulti-class Classification	CodeCode Available	5
Improving the repeatability of deep learning models with Monte Carlo dropout	Feb 15, 2022	AttributeBinary Classification	CodeCode Available	5
Exponentially Convergent Algorithms for Supervised Matrix Factorization	Nov 18, 2023	Multi-class Classification	CodeCode Available	5
Federated Learning with Only Positive Labels	Apr 21, 2020	Federated LearningMulti-class Classification	CodeCode Available	5
Competing Ratio Loss for Discriminative Multi-class Image Classification	Dec 25, 2019	Age EstimationClassification	CodeCode Available	5
Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction	May 28, 2024	Multi-class Classification	CodeCode Available	5
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning	Jun 18, 2015	General ClassificationMulti-class Classification	CodeCode Available	5
Conclusive Local Interpretation Rules for Random Forests	Apr 13, 2021	Binary ClassificationDecision Making	CodeCode Available	5
Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks	Apr 15, 2018	ClusteringMulti-class Classification	CodeCode Available	5
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case Study	Jan 30, 2024	Anomaly DetectionDataset Generation	CodeCode Available	5
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear Loss	Apr 20, 2017	Multi-class Classification	CodeCode Available	5
Evaluating approaches for supervised semantic labeling	Jan 29, 2018	BIG-bench Machine LearningData Integration	CodeCode Available	5
Conformal inference is (almost) free for neural networks trained with early stopping	Jan 27, 2023	Multi-class ClassificationOutlier Detection	CodeCode Available	5
Conformalized Semi-supervised Random Forest for Classification and Abnormality Detection	Feb 4, 2023	Anomaly DetectionMedical Diagnosis	CodeCode Available	5
Enhanced Network Embedding with Text Information	Nov 29, 2018	ClusteringMulti-class Classification	CodeCode Available	5
Consistent Structured Prediction with Max-Min Margin Markov Networks	Jul 2, 2020	Binary ClassificationGeneralization Bounds	CodeCode Available	5
A matter of attitude: Focusing on positive and active gradients to boost saliency maps	Sep 22, 2023	Multi-class Classification	CodeCode Available	5
Active Learning from Positive and Unlabeled Data	Feb 24, 2016	Active LearningInformativeness	CodeCode Available	5
AMF: Aggregated Mondrian Forests for Online Learning	Jun 25, 2019	General ClassificationMulti-class Classification	CodeCode Available	5
Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers	Aug 23, 2023	Multi-class Classification	CodeCode Available	5

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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