SOTAVerified

Multi-Label Classification

multilabel graph classification with highest result

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1026–1050 of 1198 papers

TitleStatusHype
An Empirical Evaluation of Deep Learning for ICD-9 Code Assignment using MIMIC-III Clinical NotesCode0
Deep Learning with a Rethinking Structure for Multi-label ClassificationCode0
Joint Binary Neural Network for Multi-label Learning with Applications to Emotion Classification—0
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural NetworkCode0
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models—0
Applying an Ensemble Learning Method for Improving Multi-label Classification Performance—0
Generalized Graph Embedding Models—0
Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise—0
A Scalable Deep Neural Network Architecture for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi FingerprintingCode0
Mining Supervisor Evaluation and Peer Feedback in Performance Appraisals—0
SentiNLP at IJCNLP-2017 Task 4: Customer Feedback Analysis Using a Bi-LSTM-CNN Model—0
ADAPT at IJCNLP-2017 Task 4: A Multinomial Naive Bayes Classification Approach for Customer Feedback Analysis task—0
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification—0
Intelligent EHRs: Predicting Procedure Codes From Diagnosis Codes—0
Multi-Label Zero-Shot Learning with Structured Knowledge GraphsCode0
Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification—0
Multi-label Dataless Text Classification with Topic ModelingCode0
Natural Language Informs the Interpretation of Iconic Gestures: A Computational Approach—0
Vertex-Context Sampling for Weighted Network Embedding—0
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification—0
Learning to diagnose from scratch by exploiting dependencies among labelsCode0
Similarity-based Multi-label Learning—0
Weighting Scheme for a Pairwise Multi-label Classifier Based on the Fuzzy Confusion Matrix—0
A Correction Method of a Binary Classifier Applied to Multi-label Pairwise Models—0
Using Multi-Label Classification for Improved Question AnsweringCode0
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All datasetsCheXpertMS-COCOPASCAL VOC 2007NUS-WIDEChestX-ray14OpenImages-v6PASCAL VOC 2012MLRSNetMRNetMIMIC-CXR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CFT (ensemble) Macao Polytechnic UniversityAVERAGE AUC ON 14 LABEL0.93—Unverified
2Hierarchical-Learning-V1 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
3DeepAUC-v1AVERAGE AUC ON 14 LABEL0.93—Unverified
4Conditional-Training-LSRAVERAGE AUC ON 14 LABEL0.93—Unverified
5Hierarchical-Learning-V4 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
6YWW(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
7Hierarchical-Learning-V0 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
8Conditional-Training-LSR-V1AVERAGE AUC ON 14 LABEL0.93—Unverified
9DeepCNNsGM(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
10Multi-Stage-Learning-CNN-V3 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified