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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 903 papers

TitleStatusHype
Privacy-Preserving Model and Preprocessing Verification for Machine Learning—0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context—0
Classification of Operational Records in Aviation Using Deep Learning Approaches—0
Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems—0
Towards Macro-AUC oriented Imbalanced Multi-Label Continual LearningCode0
An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning—0
Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label CorrelationsCode0
When Can Memorization Improve Fairness?—0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
Diagnosis and Severity Assessment of Ulcerative Colitis using Self Supervised Learning—0
Granular Ball K-Class Twin Support Vector Classifier—0
Does your model understand genes? A benchmark of gene properties for biological and text modelsCode1
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
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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