Text Classification On Ohsumed

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
RoBERTaGCN	72.8	BertGCN: Transductive Text Classification by Combining GCN and BERT
Our Model*	69.4	Text Level Graph Neural Network for Text Classification
SGC	68.5	Simplifying Graph Convolutional Networks
SSGC	68.5	Simple Spectral Graph Convolution
SGCN	68.5	Simplifying Graph Convolutional Networks
Text GCN	68.36	Graph Convolutional Networks for Text Classification
GraphStar	64.2	Graph Star Net for Generalized Multi-Task Learning
ApproxRepSet	64.06	Rep the Set: Neural Networks for Learning Set Representations
REL-RWMD k-NN	58.74	Speeding up Word Mover's Distance and its variants via properties of distances between embeddings
CNN+Lowercased	36.2	On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis

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Text Classification On Ohsumed | SOTA | HyperAI