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 251–300 of 903 papers

TitleStatusHype
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set ClassificationCode0
Food Classification with Convolutional Neural Networks and Multi-Class Linear Discernment AnalysisCode0
Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry PredictionCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-RaysCode0
Extrapolating Expected Accuracies for Large Multi-Class ProblemsCode0
Federated Learning with Only Positive LabelsCode0
Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance PropagationCode0
Divide and Conquer: An Ensemble Approach for Hostile Post Detection in HindiCode0
An Exploration of Softmax Alternatives Belonging to the Spherical Loss FamilyCode0
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited tripletsCode0
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear LossCode0
Distance Guided Generative Adversarial Network for Explainable Binary ClassificationsCode0
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case StudyCode0
DOLDA - a regularized supervised topic model for high-dimensional multi-class regressionCode0
Domain Adaptation with Cauchy-Schwarz DivergenceCode0
Concise Explanations of Neural Networks using Adversarial TrainingCode0
Exponentially Convergent Algorithms for Supervised Matrix FactorizationCode0
Evaluating approaches for supervised semantic labelingCode0
Explainable AI for Comparative Analysis of Intrusion Detection ModelsCode0
Ensembling Uncertainty Measures to Improve Safety of Black-Box ClassifiersCode0
Beyond Adult and COMPAS: Fairness in Multi-Class PredictionCode0
A novel Deep Learning approach for one-step Conformal Prediction approximationCode0
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic RegressionCode0
An Integer Linear Programming Framework for Mining Constraints from DataCode0
Diagnosis of COVID-19 using chest X-ray images based on modified DarkCovidNet modelCode0
Fuzzy granular approximation classifierCode0
Generalized Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary LossesCode0
Enhanced Network Embedding with Text InformationCode0
Financial Data Analysis with Robust Federated Logistic RegressionCode0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
HemaGraph: Breaking Barriers in Hematologic Single Cell Classification with Graph AttentionCode0
Semi-supervised Vector-valued Learning: Improved Bounds and AlgorithmsCode0
Optimal-margin evolutionary classifierCode0
Detection of Suicidal Risk on Social Media: A Hybrid Model—0
Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilities—0
Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach—0
Detecting Tweets Reporting Birth Defect Pregnancy Outcome Using Two-View CNN RNN Based Architecture—0
Detecting Throat Cancer from Speech Signals using Machine Learning: A Scoping Literature Review—0
Bayes-optimal Hierarchical Classification over Asymmetric Tree-Distance Loss—0
An Effective Approach for Multi-label Classification with Missing Labels—0
Detecting immune cells with label-free two-photon autofluorescence and deep learning—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
Described Spatial-Temporal Video Detection—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
Dermoscopic Image Analysis for ISIC Challenge 2018—0
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification—0
Degrees of Freedom in Deep Neural Networks—0
An Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures—0
Show:102550
← PrevPage 6 of 19Next →
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