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 251–300 of 903 papers

TitleStatusHype
Detecting Throat Cancer from Speech Signals using Machine Learning: A Scoping Literature Review—0
Detecting Tweets Reporting Birth Defect Pregnancy Outcome Using Two-View CNN RNN Based Architecture—0
Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilities—0
Detection of Suicidal Risk on Social Media: A Hybrid Model—0
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning—0
Apple Counting using Convolutional Neural Networks—0
Classified as unknown: A novel Bayesian neural network—0
Classification with many classes: challenges and pluses—0
A generalized flow for multi-class and binary classification tasks: An Azure ML approach—0
Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models—0
Classification of Operational Records in Aviation Using Deep Learning Approaches—0
Classification based on Topological Data Analysis—0
A One-Sided Classification Toolkit with Applications in the Analysis of Spectroscopy Data—0
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker—0
An Unsupervised Domain-Independent Framework for Automated Detection of Persuasion Tactics in Text—0
A Generalization Error Bound for Multi-class Domain Generalization—0
Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN—0
Filtering Aggression from the Multilingual Social Media Feed—0
Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rays—0
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing—0
Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-class Classification with a Convolutional Neural Network—0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
Cascading Machine Learning to Attack Bitcoin Anonymity—0
A Novel Progressive Learning Technique for Multi-class Classification—0
A Gegenbauer Neural Network with Regularized Weights Direct Determination for Classification—0
Capsules as viewpoint learners for human pose estimation—0
A Novel Online Real-time Classifier for Multi-label Data Streams—0
A novel online multi-label classifier for high-speed streaming data applications—0
A Fully Memristive Spiking Neural Network with Unsupervised Learning—0
Aanisha@TamilNLP-ACL2022:Abusive Detection in Tamil—0
Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation—0
Enhanced H-Consistency Bounds—0
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem—0
On the computational complexity of the probabilistic label tree algorithms—0
End-to-End Automatic Speech Recognition with Deep Mutual Learning—0
Explainable Multi-class Classification of the CAMH COVID-19 Mental Health Data—0
Explicit Facial Expression Transfer via Fine-Grained Representations—0
Active Learning for Structured Probabilistic Models With Histogram Approximation—0
Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification—0
EMG Signal Classification for Neuromuscular Disorders with Attention-Enhanced CNN—0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
A Novel Adaptive Hybrid Focal-Entropy Loss for Enhancing Diabetic Retinopathy Detection Using Convolutional Neural Networks—0
Elimination of All Bad Local Minima in Deep Learning—0
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification—0
Building an Interpretable Recommender via Loss-Preserving Transformation—0
Bridging Social Media via Distant Supervision—0
Energy-based features and bi-LSTM neural network for EEG-based music and voice classification—0
Energy-based Out-of-distribution Detection for Multi-label Classification—0
Efficient or Powerful? Trade-offs Between Machine Learning and Deep Learning for Mental Illness Detection on Social Media—0
A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data—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