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 251–300 of 903 papers

TitleStatusHype
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection—0
Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN—0
Probabilistic Truly Unordered Rule SetsCode0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
SemEval-2017 Task 4: Sentiment Analysis in Twitter using BERTCode0
Harnessing Deep Learning and Satellite Imagery for Post-Buyout Land Cover Mapping—0
Safe reinforcement learning in uncertain contextsCode0
Distance Guided Generative Adversarial Network for Explainable Binary ClassificationsCode0
Reading Between the Leads: Local Lead-Attention Based Classification of Electrocardiogram SignalsCode0
Aspect category learning and sentimental analysis using weakly supervised learning—0
MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image DeformationsCode0
NearbyPatchCL: Leveraging Nearby Patches for Self-Supervised Patch-Level Multi-Class Classification in Whole-Slide ImagesCode0
Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class ClassificationCode0
Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsCode0
Improving Bias Mitigation through Bias Experts in Natural Language UnderstandingCode0
Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach—0
Quantum Neural Networks under Depolarization Noise: Exploring White-Box Attacks and Defenses—0
PMP-Swin: Multi-Scale Patch Message Passing Swin Transformer for Retinal Disease Classification—0
Exponentially Convergent Algorithms for Supervised Matrix FactorizationCode0
Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning—0
Image Classification using Combination of Topological Features and Neural Networks—0
Auto deep learning for bioacoustic signalsCode0
Understanding Deep Representation Learning via Layerwise Feature Compression and DiscriminationCode0
Learning Robust Sequential Recommenders through Confident Soft LabelsCode0
Efficient Machine Learning Ensemble Methods for Detecting Gravitational Wave Glitches in LIGO Time SeriesCode0
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?—0
Performance Improvement in Multi-class Classification via Automated Hierarchy Generation and Exploitation through Extended LCPN Schemes—0
Breaking the Token Barrier: Chunking and Convolution for Efficient Long Text Classification with BERT—0
Support matrix machine: A review—0
Neural Collapse in Multi-label Learning with Pick-all-label LossCode0
Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms—0
Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention—0
Powerset multi-class cross entropy loss for neural speaker diarization—0
Utilizing Weak Supervision To Generate Indonesian Conservation Dataset—0
Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label ClassificationCode0
Open-Set Knowledge-Based Visual Question Answering with Inference PathsCode0
Pool-Based Active Learning with Proper Topological Regions—0
QUILT: Effective Multi-Class Classification on Quantum Computers Using an Ensemble of Diverse Quantum Classifiers—0
A matter of attitude: Focusing on positive and active gradients to boost saliency mapsCode0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
EMG Signal Classification for Neuromuscular Disorders with Attention-Enhanced CNN—0
New Bounds on the Accuracy of Majority Voting for Multi-Class Classification—0
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection—0
A Multi-In and Multi-Out Dendritic Neuron Model and its Optimization—0
Respiratory Disease Classification and Biometric Analysis Using Biosignals from Digital Stethoscopes—0
Spatial encoding of BOLD fMRI time series for categorizing static images across visual datasets: A pilot study on human visionCode0
Graph-Based Automatic Feature Selection for Multi-Class Classification via Mean Simplified Silhouette—0
Application of Quantum Pre-Processing Filter for Binary Image Classification with Small SamplesCode0
Ensembling Uncertainty Measures to Improve Safety of Black-Box ClassifiersCode0
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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