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 226–250 of 903 papers

TitleStatusHype
A Deep Generative Approach to Native Language Identification—0
Deep Attention Model for Triage of Emergency Department Patients—0
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables—0
Automated diagnosis of lung diseases using vision transformer: a comparative study on chest x-ray classification—0
Deep Convolutional Neural Network based Classification of Alzheimer's Disease using MRI data—0
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning—0
Deep Learning Approaches for Blood Disease Diagnosis Across Hematopoietic Lineages—0
Deep Learning-based automated classification of Chinese Speech Sound Disorders—0
Deep Learning-Based Intra Mode Derivation for Versatile Video Coding—0
Apple Counting using Convolutional Neural Networks—0
Deep Multi Label Classification in Affine Subspaces—0
Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks—0
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy—0
Deep reinforced active learning for multi-class image classification—0
Deep Sequence Models for Text Classification Tasks—0
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis—0
Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification—0
An Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures—0
Degrees of Freedom in Deep Neural Networks—0
Classified as unknown: A novel Bayesian neural network—0
Dermoscopic Image Analysis for ISIC Challenge 2018—0
Described Spatial-Temporal Video Detection—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
Detecting immune cells with label-free two-photon autofluorescence and deep learning—0
Classification with many classes: challenges and pluses—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