Incident Detection on Waze reports (5-fold CV)
0.4PrecisionLogistic Regression
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| Logistic RegressionModel ID=M4, Features=Plausibility (Clustering-based), Category=Proposed2020.11 | 0.4 | 0.56 | 0.35 | 0.69 | |
| Random ForestModel ID=M3, Features=Plausibility (Clustering-based), Category=Proposed2020.11 | 0.37 | 0.64 | 0.34 | 0.69 | |
| Random ForestModel ID=M5, Features=Plausibility (Segmentation-based), Category=Proposed2020.11 | 0.36 | 0.67 | 0.47 | 0.65 | |
| Logistic RegressionModel ID=M6, Features=Plausibility (Segmentation-based), Category=Proposed2020.11 | 0.36 | 0.7 | 0.48 | 0.66 | |
| Logistic RegressionModel ID=M10, Features=All (Segmentation-based), Category=Proposed2020.11 | 0.36 | 0.69 | 0.47 | 0.68 | |
| Random ForestModel ID=M9, Features=All (Segmentation-based), Category=Proposed2020.11 | 0.35 | 0.72 | 0.47 | 0.68 | |
| Logistic RegressionModel ID=M2, Features=Avg. Reliability & Count, Category=Baseline2020.11 | 0.34 | 0.68 | 0.45 | 0.65 | |
| Random ForestModel ID=M1, Features=Avg. Reliability & Count, Category=Baseline2020.11 | 0.31 | 0.78 | 0.44 | 0.64 | |
| Random ForestModel ID=M7, Features=All (Clustering-based), Category=Proposed2020.11 | 0.3 | 0.7 | 0.37 | 0.71 | |
| Logistic RegressionModel ID=M8, Features=All (Clustering-based), Category=Proposed2020.11 | 0.3 | 0.66 | 0.36 | 0.71 |