Research Article
Speeding Violation Type Prediction Based on Decision Tree Method: A Case Study in Wujiang, China
Table 2
Binary logistic regression analysis results.
| | Factor | df | P value | OR | 95.0% CI for OR | | Lower | Upper |
| | License plate 1 (base: license plate (0)) | 1 | 0.000 | 1.238 | 1.156 | 1.326 | | Season (base: season (0)) | 3 | 0.000 | | | | | season (1) | 1 | 0.002 | 0.876 | 0.806 | 0.952 | | season (2) | 1 | 0.000 | 2.309 | 2.159 | 2.470 | | season (3) | 1 | 0.020 | 0.896 | 0.816 | 0.983 | | Speeding area (base: speeding area (0)) | 3 | 0.000 | | | | | speeding area (1) | 1 | 0.000 | 0.516 | 0.394 | 0.676 | | speeding area (2) | 1 | 0.001 | 1.643 | 1.221 | 2.210 | | speeding area (3) | 1 | 0.053 | 2.828 | 0.986 | 8.112 | | Position (base: position (0)) | 3 | 0.000 | | | | | position (1) | 1 | 0.000 | 0.759 | 0.691 | 0.833 | | position (2) | 1 | 0.000 | 1.517 | 1.312 | 1.754 | | position (3) | 1 | 0.267 | 0.925 | 0.806 | 1.062 | | Rainfall (base: rain (0)) | 3 | 0.000 | | | | | rainfall (1) | 1 | 0.000 | 1.286 | 1.174 | 1.409 | | rainfall (2) | 1 | 0.137 | 1.278 | 0.925 | 1.767 | | rainfall (3) | 1 | 0.004 | 2.810 | 1.380 | 5.725 |
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