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 251–275 of 903 papers

TitleStatusHype
Venn Diagram Multi-label Class Interpretation of Diabetic Foot Ulcer with Color and Sharpness Enhancement—0
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression—0
UCF: Uncovering Common Features for Generalizable Deepfake DetectionCode3
T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer ClassificationCode0
Vision-based Estimation of Fatigue and Engagement in Cognitive Training SessionsCode0
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus ImagesCode0
Multi-label Node Classification On Graph-Structured DataCode1
Performance of GAN-based augmentation for deep learning COVID-19 image classificationCode0
MisRoBÆRTa: Transformers versus MisinformationCode0
1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge—0
Learning Optimal Fair Scoring Systems for Multi-Class Classification—0
KeyDetect --Detection of anomalies and user based on Keystroke Dynamics—0
A BERT-based Unsupervised Grammatical Error Correction Framework—0
Neuro-symbolic Rule Learning in Real-world Classification TasksCode0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
Automatic pain recognition from Blood Volume Pulse (BVP) signal using machine learning techniques—0
DPPMask: Masked Image Modeling with Determinantal Point Processes—0
Transformer Models for Acute Brain Dysfunction Prediction—0
Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language ModelsCode1
Machine learning tools to improve nonlinear modeling parameters of RC columns—0
Graph-based Extreme Feature Selection for Multi-class Classification Tasks—0
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations?—0
FLAG: Fast Label-Adaptive Aggregation for Multi-label Classification in Federated Learning—0
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image DetectionCode1
MVMTnet: A Multi-variate Multi-modal Transformer for Multi-class Classification of Cardiac Irregularities Using ECG Waveforms and Clinical NotesCode1
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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
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1SVM (tficf)Macro F173.9—Unverified
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1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified