Classification on Zoo UCI (test)
95.3PrecisionSparse Tensor Classifier Quantum (STC-Q)
Evaluation results
| Method | Links | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sparse Tensor Classifier Quantum (STC-Q)h=1, b=1, p=1/2, probability=quantum, runs=1002021.05 | 95.3 | 95.3 | 94.5 | 87.1 | 62 | 66 | 75 | 61 | 87 | 61 | 100 | 0 | 64 | |
| Support Vector Machine (SVM)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 94.6 | 94.1 | 93.4 | 84.7 | 50 | 68 | 71 | 0 | 79 | 52 | 96 | 39 | 57 | |
| Logistic Regression (LR)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 94.6 | 93.8 | 93.2 | 84.3 | 46 | 62 | 72 | 48 | 78 | 0 | 96 | 39 | 55 | |
| Decision Tree (DT)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 94.4 | 93.5 | 93.1 | 83.6 | 0 | 61 | 73 | 50 | 80 | 54 | 97 | 38 | 57 | |
| Random Forest (RF)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 93.6 | 93.1 | 92.3 | 82.7 | 39 | 0 | 70 | 32 | 72 | 38 | 98 | 34 | 48 | |
| K-Nearest Neighbors (KNN)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 91.6 | 91.5 | 90.5 | 79.2 | 27 | 30 | 0 | 29 | 63 | 28 | 96 | 25 | 37 | |
| Multinomial Naive Bayes (MNB)implementation=scikit-learn, tuning=grid search on weighted f1-score, runs=1002021.05 | 91.6 | 90.3 | 89.7 | 76.4 | 20 | 28 | 37 | 21 | 0 | 22 | 86 | 13 | 28 | |
| Sparse Tensor Classifier Classic (STC-C)h=1, b=0, p=1, probability=classical, runs=1002021.05 | 79 | 85 | 80.4 | 65.9 | 3 | 2 | 4 | 4 | 14 | 4 | 0 | 0 | 4 |