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 151–200 of 903 papers

TitleStatusHype
When Can Memorization Improve Fairness?—0
Diagnosis and Severity Assessment of Ulcerative Colitis using Self Supervised Learning—0
Granular Ball K-Class Twin Support Vector Classifier—0
An In-Depth Examination of Risk Assessment in Multi-Class Classification Algorithms—0
Learning from Concealed LabelsCode0
FD-LLM: Large Language Model for Fault Diagnosis of Machines—0
Bi-Band ECoGNet for ECoG Decoding on Classification Task—0
Training Multi-Layer Binary Neural Networks With Local Binary Error Signals—0
Breast Tumor Classification Using EfficientNet Deep Learning ModelCode0
Comparative Analysis of Resource-Efficient CNN Architectures for Brain Tumor Classification—0
A Data-Driven Pool Strategy for Price-Makers Under Imperfect Information—0
Energy-based features and bi-LSTM neural network for EEG-based music and voice classification—0
Machine Learning Evaluation Metric Discrepancies across Programming Languages and Their Components: Need for Standardization—0
A Novel Adaptive Hybrid Focal-Entropy Loss for Enhancing Diabetic Retinopathy Detection Using Convolutional Neural Networks—0
DT-JRD: Deep Transformer based Just Recognizable Difference Prediction Model for Video Coding for Machines—0
Model agnostic local variable importance for locally dependent relationships—0
Performance-Guided LLM Knowledge Distillation for Efficient Text Classification at Scale—0
Generalization and Risk Bounds for Recurrent Neural Networks—0
FoLDTree: A ULDA-Based Decision Tree Framework for Efficient Oblique Splits and Feature Selection—0
Advancing Efficient Brain Tumor Multi-Class Classification -- New Insights from the Vision Mamba Model in Transfer Learning—0
Comment on Is Complexity an Illusion?—0
Multi-Class Abnormality Classification in Video Capsule Endoscopy Using Deep LearningCode0
Integrating Deep Feature Extraction and Hybrid ResNet-DenseNet Model for Multi-Class Abnormality Detection in Endoscopic Images—0
Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurement—0
Machine learning approach to brain tumor detection and classification—0
Beyond Labels: A Self-Supervised Framework with Masked Autoencoders and Random Cropping for Breast Cancer Subtype Classification—0
SciPrompt: Knowledge-augmented Prompting for Fine-grained Categorization of Scientific TopicsCode0
Effective Intrusion Detection for UAV Communications using Autoencoder-based Feature Extraction and Machine Learning Approach—0
Insight: A Multi-Modal Diagnostic Pipeline using LLMs for Ocular Surface Disease Diagnosis—0
Interpretable Rule-Based System for Radar-Based Gesture Sensing: Enhancing Transparency and Personalization in AI—0
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer LearningCode0
More Consideration for the PerceptronCode0
Enhancing Personalized Recipe Recommendation Through Multi-Class Classification—0
Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilities—0
Self-supervised Multimodal Speech Representations for the Assessment of Schizophrenia Symptoms—0
Constrained Multi-Layer Contrastive Learning for Implicit Discourse Relationship Recognition—0
Multi-Output Distributional Fairness via Post-Processing—0
Obfuscated Memory Malware Detection—0
Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and MethodCode0
Combining features on vertical ground reaction force signal analysis for multiclass diagnosing neurodegenerative diseases—0
pSVM: Soft-margin SVMs with p-norm Hinge LossCode0
Neural CRNs: A Natural Implementation of Learning in Chemical Reaction NetworksCode0
SCREENER: A general framework for task-specific experiment design in quantitative MRI—0
Graph Residual based Method for Molecular Property Prediction—0
On the Utility of Speech and Audio Foundation Models for Marmoset Call AnalysisCode0
Regression under demographic parity constraints via unlabeled post-processing—0
Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach—0
Enhanced H-Consistency Bounds—0
Word Embedding Dimension Reduction via Weakly-Supervised Feature SelectionCode0
Weighted Aggregation of Conformity Scores for Classification—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