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 101–125 of 903 papers

TitleStatusHype
Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech—0
Detection of Suicidal Risk on Social Media: A Hybrid Model—0
DECT-based Space-Squeeze Method for Multi-Class Classification of Metastatic Lymph Nodes in Breast CancerCode0
AppealCase: A Dataset and Benchmark for Civil Case Appeal ScenariosCode0
Self-Classification Enhancement and Correction for Weakly Supervised Object Detection—0
Neuro-Argumentative Learning with Case-Based ReasoningCode0
Efficient Malicious UAV Detection Using Autoencoder-TSMamba Integration—0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
In-Context Learning for Label-Efficient Cancer Image Classification in Oncology—0
TunnElQNN: A Hybrid Quantum-classical Neural Network for Efficient Learning—0
Light Weight CNN for classification of Brain Tumors from MRI Images—0
Financial Data Analysis with Robust Federated Logistic RegressionCode0
ThyroidEffi 1.0: A Cost-Effective System for High-Performance Multi-Class Thyroid Carcinoma Classification—0
Multi-output Classification Framework and Frequency Layer Normalization for Compound Fault Diagnosis in Motor—0
TabKAN: Advancing Tabular Data Analysis using Kolmogorov-Arnold Network—0
Quantum neural networks facilitating quantum state classification—0
PRACH Preamble Detection as a Multi-Class Classification Problem: A Machine Learning Approach Using SVM—0
Leveraging Embedding Techniques in Multimodal Machine Learning for Mental Illness Assessment—0
Measuring Online Hate on 4chan using Pre-trained Deep Learning Models—0
SKDU at De-Factify 4.0: Natural Language Features for AI-Generated Text-DetectionCode0
Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining—0
Deep Learning Approaches for Blood Disease Diagnosis Across Hematopoietic Lineages—0
Quantum Complex-Valued Self-Attention Model—0
Automated diagnosis of lung diseases using vision transformer: a comparative study on chest x-ray classification—0
Probabilistic Quantum SVM Training on Ising Machine—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