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 326–350 of 903 papers

TitleStatusHype
Decentralized Online Learning with Kernels—0
A Multi-Task Self-Normalizing 3D-CNN to Infer Tuberculosis Radiological Manifestations—0
A Deep Generative Approach to Native Language Identification—0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context—0
DCSVM: Fast Multi-class Classification using Support Vector Machines—0
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference—0
Data-driven root-cause analysis for distributed system anomalies—0
Data-Driven Fault Diagnosis Analysis and Open-Set Classification of Time-Series Data—0
A Universal Growth Rate for Learning with Smooth Surrogate Losses—0
A Multi-Plant Disease Diagnosis Method using Convolutional Neural Network—0
Data-dependent Generalization Bounds for Multi-class Classification—0
CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks—0
Cut your Losses with Squentropy—0
Curriculum Learning for Speech Emotion Recognition from Crowdsourced Labels—0
Respiratory Disease Classification and Biometric Analysis Using Biosignals from Digital Stethoscopes—0
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization—0
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements—0
Revisiting Classification Perspective on Scene Text Recognition—0
A Tutorial on the Pretrain-Finetune Paradigm for Natural Language Processing—0
Cross-domain Recommendation via Deep Domain Adaptation—0
Critical Review for One-class Classification: recent advances and the reality behind them—0
Attention-based Region of Interest (ROI) Detection for Speech Emotion Recognition—0
A multi-label, dual-output deep neural network for automated bug triaging—0
CPS Attack Detection under Limited Local Information in Cyber Security: A Multi-node Multi-class Classification Ensemble Approach—0
COV-ELM classifier: An Extreme Learning Machine based identification of COVID-19 using Chest X-Ray Images—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
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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