Text Classification on 20 Newsgroups by-date (test)
87.3AccuracySTC-Q
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| STC-QHyper-parameter p=1/3, Vectorization scheme=None (direct on terms), Hyper-parameter Tuning=modified quantum probability amplitude2021.05 | 87.3 | 87.1 | 86.8 | 86.6 | |
| Diversified Ensemble Neural Network (DEns)Hyper-parameter Tuning=specifically tuned2021.05 | 87.1 | — | — | — | |
| Neural Attentive Bag-of-Entities Model (NABOE)Hyper-parameter Tuning=specifically tuned2021.05 | 86.8 | — | — | 86.2 | |
| STC-QHyper-parameter p=1/2, Vectorization scheme=None (direct on terms), Hyper-parameter Tuning=standard configuration2021.05 | 86.4 | 86.3 | 85.6 | 85.6 | |
| TextEntHyper-parameter Tuning=specifically tuned2021.05 | 84.5 | — | — | 83.9 | |
| Cooperative Neural Networks (CoNN)Hyper-parameter Tuning=specifically tuned2021.05 | 83.7 | — | — | — | |
| Logistic Regression (LR)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 80.5 | 80.8 | 79.5 | 79.7 | |
| Support Vector Machine (SVM)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 78.8 | 79.9 | 77.9 | 78.4 | |
| Multinomial Naive Bayes (MNB)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 74.4 | 82.2 | 72.5 | 72.4 | |
| Random Forest (RF)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 73.9 | 74.8 | 72.7 | 72.5 | |
| Decision Tree (DT)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 54.9 | 54.6 | 54.3 | 54.3 | |
| K-Nearest Neighbors (KNN)Vectorization scheme=Tf-Idf, Hyper-parameter Tuning=default scikit-learn2021.05 | 52.9 | 59.9 | 52.8 | 53.9 |