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 626–650 of 903 papers

TitleStatusHype
Adversarial Multi-Binary Neural Network for Multi-class Classification—0
Multi-Class classification of vulnerabilities in Smart Contracts using AWD-LSTM, with pre-trained encoder inspired from natural language processing—0
Diagnosis of Diabetic Retinopathy in Ethiopia: Before the Deep Learning based Automation—0
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift—0
On the Learning Property of Logistic and Softmax Losses for Deep Neural NetworksCode0
Comparison of Multi-Class and Binary Classification Machine Learning Models in Identifying Strong Gravitational Lenses—0
Imbalance Learning for Variable Star ClassificationCode0
On the generalization of bayesian deep nets for multi-class classification—0
Optimistic bounds for multi-output prediction—0
The Utility of General Domain Transfer Learning for Medical Language Tasks—0
Multi-Class Classification from Noisy-Similarity-Labeled Data—0
Improving automated segmentation of radio shows with audio embeddings—0
A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data—0
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing—0
Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-class Classification with a Convolutional Neural Network—0
Multi-Participant Multi-Class Vertical Federated Learning—0
Optimistic bounds for multi-output learning—0
Transparency Promotion with Model-Agnostic Linear Competitors—0
Competing Ratio Loss for Discriminative Multi-class Image ClassificationCode0
An Unsupervised Domain-Independent Framework for Automated Detection of Persuasion Tactics in Text—0
Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning—0
Sequential Classification with Empirically Observed Statistics—0
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements—0
Primal-Dual Block Generalized Frank-WolfeCode0
Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks—0
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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
#ModelMetricClaimedVerifiedStatus
1SVM (tficf)Macro F173.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified