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 376–400 of 903 papers

TitleStatusHype
MultiGuard: Provably Robust Multi-label Classification against Adversarial ExamplesCode0
Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data—0
UB Health Miners@SMM4H’22: Exploring Pre-processing Techniques To Classify Tweets Using Transformer Based Pipelines.—0
Is Encoder-Decoder Transformer the Shiny Hammer?—0
Class-Imbalanced Complementary-Label Learning via Weighted Loss—0
Source detection via multi-label classificationCode0
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing AccuracyCode0
MulBot: Unsupervised Bot Detection Based on Multivariate Time Series—0
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian ManifoldCode0
Upper bounds on the Natarajan dimensions of some function classes—0
Semantic Interactive Learning for Text Classification: A Constructive Approach for Contextual InteractionsCode0
Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing LabelsCode0
CPS Attack Detection under Limited Local Information in Cyber Security: A Multi-node Multi-class Classification Ensemble Approach—0
Apple Counting using Convolutional Neural Networks—0
Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning—0
Semi-Supervised Anomaly Detection Based on Quadratic Multiform Separation—0
FOLD-SE: An Efficient Rule-based Machine Learning Algorithm with Scalable Explainability—0
TagRec++: Hierarchical Label Aware Attention Network for Question CategorizationCode0
Retrieval of surgical phase transitions using reinforcement learning—0
Factorizable Joint Shift in Multinomial Classification—0
A novel Deep Learning approach for one-step Conformal Prediction approximationCode0
Deep Sequence Models for Text Classification Tasks—0
Learning Mutual Fund Categorization using Natural Language Processing—0
Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk RegularizationCode0
University of Bucharest Team at Semeval-2022 Task4: Detection and Classification of Patronizing and Condescending Language—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