Analysis and Detection of Road Traffic Accident Severity via Data Mining Techniques: Case Study Addis Ababa, Ethiopia

Table 4

Rules generated from the frequent itemset and their confidence.

Rules	Confidence (%)
(Gender: male) ^ (driver–vehicle relation: employee) ^ (weather condition: normal) ^ (pedestrian movement: not a pedestrian) ^ (road surface type: asphalt) ⟶ (accident severity: high)	84.35
(Gender: male) ^ (driver–vehicle relation: employee) ^ (weather condition: normal) ⟶ (pedestrian movement: not a pedestrian) ^ (road surface type: asphalt) ^ (accident severity: high)	71.34
(Gender: male) ^ (driver–vehicle relation: employee) ^ (weather condition: normal) ^ (pedestrian movement: not a pedestrian) ⟶ (road surface type: asphalt) ^ (accident severity: high)	77.42