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 601–650 of 903 papers

TitleStatusHype
University of Bucharest Team at Semeval-2022 Task4: Detection and Classification of Patronizing and Condescending Language—0
Unsupervised Adversarial Invariance—0
Upper bounds on the Natarajan dimensions of some function classes—0
Using Ranking-CNN for Age Estimation—0
Utilizing Weak Supervision To Generate Indonesian Conservation Dataset—0
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis—0
Venn Diagram Multi-label Class Interpretation of Diabetic Foot Ulcer with Color and Sharpness Enhancement—0
Violence Detection in Videos—0
Visualizing CoAtNet Predictions for Aiding Melanoma Detection—0
Walk in Wild: An Ensemble Approach for Hostility Detection in Hindi Posts—0
Want to Identify, Extract and Normalize Adverse Drug Reactions in Tweets? Use RoBERTa—0
Weighted Aggregation of Conformity Scores for Classification—0
When Can Memorization Improve Fairness?—0
When Unsupervised Domain Adaptation meets One-class Anomaly Detection: Addressing the Two-fold Unsupervised Curse by Leveraging Anomaly Scarcity—0
Word Vector Enrichment of Low Frequency Words in the Bag-of-Words Model for Short Text Multi-class Classification Problems—0
Wound Severity Classification using Deep Neural Network—0
X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications—0
Yelp Dataset Challenge: Review Rating Prediction—0
Classification and Detection in Mammograms with Weak Supervision via Dual Branch Deep Neural Net—0
Zero-shot Active Learning with Topological Clustering for Multiclass Classification—0
On the computational complexity of the probabilistic label tree algorithms—0
1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge—0
200K+ Crowdsourced Political Arguments for a New Chilean Constitution—0
Efficient Malicious UAV Detection Using Autoencoder-TSMamba Integration—0
3D Shape Classification Using Collaborative Representation based Projections—0
Aanisha@TamilNLP-ACL2022:Abusive Detection in Tamil—0
A Bayesian Approach for Accurate Classification-Based Aggregates—0
A BERT-based Unsupervised Grammatical Error Correction Framework—0
A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection—0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context—0
A comprehensive solution to retrieval-based chatbot construction—0
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models—0
Adaptive Multinomial Matrix Completion—0
A Data-Driven Pool Strategy for Price-Makers Under Imperfect Information—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements—0
A Deep Generative Approach to Native Language Identification—0
Weakly and Semi Supervised Detection in Medical Imaging via Deep Dual Branch Net—0
Advancing Efficient Brain Tumor Multi-Class Classification -- New Insights from the Vision Mamba Model in Transfer Learning—0
Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification—0
Adversarial Multi-Binary Neural Network for Multi-class Classification—0
Affinity-Based Hierarchical Learning of Dependent Concepts for Human Activity Recognition—0
A Fully Memristive Spiking Neural Network with Unsupervised Learning—0
A Gegenbauer Neural Network with Regularized Weights Direct Determination for Classification—0
A Generalization Error Bound for Multi-class Domain Generalization—0
A generalized flow for multi-class and binary classification tasks: An Azure ML approach—0
A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling—0
A High Speed Multi-label Classifier based on Extreme Learning Machines—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