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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 126–150 of 903 papers

TitleStatusHype
Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach—0
A Multi-Plant Disease Diagnosis Method using Convolutional Neural Network—0
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization—0
Respiratory Disease Classification and Biometric Analysis Using Biosignals from Digital Stethoscopes—0
A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements—0
Comparative Analysis of Resource-Efficient CNN Architectures for Brain Tumor Classification—0
A Tutorial on the Pretrain-Finetune Paradigm for Natural Language Processing—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
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
A Multi-In and Multi-Out Dendritic Neuron Model and its Optimization—0
A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection—0
Comment on Is Complexity an Illusion?—0
Comparison of Decision Tree Based Classification Strategies to Detect External Chemical Stimuli from Raw and Filtered Plant Electrical Response—0
ATESA-BÆRT: A Heterogeneous Ensemble Learning Model for Aspect-Based Sentiment Analysis—0
A Survey on Open Set Recognition—0
A multi-class structured dictionary learning method using discriminant atom selection—0
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem—0
Aspect category learning and sentimental analysis using weakly supervised learning—0
A Data-Driven Pool Strategy for Price-Makers Under Imperfect Information—0
Combining features on vertical ground reaction force signal analysis for multiclass diagnosing neurodegenerative diseases—0
A simple technique for improving multi-class classification with neural networks—0
Efficient Malicious UAV Detection Using Autoencoder-TSMamba Integration—0
Classification and Detection in Mammograms with Weak Supervision via Dual Branch Deep Neural Net—0
A scalable stage-wise approach to large-margin multi-class loss based boosting—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