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 51–100 of 903 papers

TitleStatusHype
Self-supervised Spatial Reasoning on Multi-View Line DrawingsCode1
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent ApplicationsCode1
Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack MusicCode1
Towards Good Practices for Efficiently Annotating Large-Scale Image Classification DatasetsCode1
Does your model understand genes? A benchmark of gene properties for biological and text modelsCode1
Uncertainty Calibration with Energy Based Instance-wise Scaling in the Wild DatasetCode1
A Deep Neural Network for SSVEP-based Brain-Computer InterfacesCode1
Unknown Prompt the only Lacuna: Unveiling CLIP's Potential for Open Domain GeneralizationCode1
VenusX: Unlocking Fine-Grained Functional Understanding of ProteinsCode1
VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail CheckoutCode1
What Makes Graph Neural Networks Miscalibrated?Code1
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelCode1
Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?Code1
Can multi-label classification networks know what they don’t know?Code1
CIGAN: A Python Package for Handling Class Imbalance using Generative Adversarial NetworksCode1
BAdaCost: Multi-class Boosting with CostsCode1
Co-attention network with label embedding for text classificationCode1
Constrained Optimization to Train Neural Networks on Critical and Under-Represented ClassesCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertaintyCode1
Dual-Objective Fine-Tuning of BERT for Entity MatchingCode1
Efficient Set-Valued Prediction in Multi-Class ClassificationCode1
A Novel Approach for detecting Normal, COVID-19 and Pneumonia patient using only binary classifications from chest CT-ScansCode1
A Fully Hyperbolic Neural Model for Hierarchical Multi-Class ClassificationCode1
Enumerating the k-fold configurations in multi-class classification problemsCode1
Event-Event Relation Extraction using Probabilistic Box EmbeddingCode1
Explainable Causal Analysis of Mental Health on Social Media DataCode1
Exploiting Class Activation Value for Partial-Label LearningCode1
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental LearningCode1
GraphHop: An Enhanced Label Propagation Method for Node ClassificationCode1
Can multi-label classification networks know what they don't know?Code1
Hyper Evidential Deep Learning to Quantify Composite Classification UncertaintyCode1
Automated detection of COVID-19 cases using deep neural networks with X-ray imagesCode1
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer ClassificationCode1
A Practioner's Guide to Evaluating Entity Resolution ResultsCode1
IoTDevID: A Behavior-Based Device Identification Method for the IoTCode1
One-Class Risk Estimation for One-Class Hyperspectral Image ClassificationCode1
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More PracticalCode1
Clinical Relation Extraction Using Transformer-based ModelsCode1
Multi-class Gaussian Process Classification with Noisy InputsCode1
Multimodal Attention-based Deep Learning for Alzheimer's Disease DiagnosisCode1
MVMTnet: A Multi-variate Multi-modal Transformer for Multi-class Classification of Cardiac Irregularities Using ECG Waveforms and Clinical NotesCode1
One-step and Two-step Classification for Abusive Language Detection on TwitterCode1
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image DetectionCode1
DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and ClassificationCode1
PMLB v1.0: An open source dataset collection for benchmarking machine learning methodsCode1
An Effective Approach for Multi-label Classification with Missing Labels—0
An Attention-based Long Short-Term Memory Framework for Detection of Bitcoin Scams—0
Advancing Efficient Brain Tumor Multi-Class Classification -- New Insights from the Vision Mamba Model in Transfer Learning—0
An Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures—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
#ModelMetricClaimedVerifiedStatus
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