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 811–820 of 903 papers

Title	Date	Tasks	Status
Comparison of Decision Tree Based Classification Strategies to Detect External Chemical Stimuli from Raw and Filtered Plant Electrical Response	May 13, 2017	ClassificationGeneral Classification	—Unverified
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear Loss	Apr 20, 2017	Multi-class Classification	CodeCode Available
Classifying Lexical-semantic Relationships by Exploiting Sense/Concept Representations	Apr 1, 2017	General ClassificationMulti-class Classification	—Unverified
Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks	Mar 29, 2017	General ClassificationMulti-class Classification	—Unverified
Randomized Kernel Methods for Least-Squares Support Vector Machines	Mar 22, 2017	ClassificationGeneral Classification	—Unverified
Computer Aided Detection of Anemia-like Pallor	Mar 17, 2017	BenchmarkingClassification	—Unverified
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy	Feb 27, 2017	Brain SegmentationMulti-class Classification	—Unverified
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification	Jan 23, 2017	Binary ClassificationClassification	CodeCode Available
GenSVM: A Generalized Multiclass Support Vector Machine	Dec 30, 2016	Multi-class Classification	CodeCode Available
An Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures	Dec 5, 2016	Multi-class Classification	—Unverified

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All datasets COVID-19 CXR Dataset COVID chest X-ray Reuters-52 TII-SSRC-23 Training and validation dataset of capsule vision 2024 challenge.

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	COVID-CXNet	Accuracy (%)	94.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	COVID-ResNet	F1 score	0.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SVM (tficf)	Macro F1	73.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Extra Trees	F1-Score	93.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multi-Model Ensemble	Mean AUC	0.99	—	Unverified