Table 2 Summary of results of models predicting the traffic status after 6 h on our study’s street.

From: Predicting vehicle travel time on city streets for trip preplanning and predicting heavy traffic for proactive control of street congestion

 

AdaBoost 

Neural net. 

Gradient boost. 

Nearest neighbors 

Support vect. mach.

Accuracy score

0.9805

0.9840

0.9826

0.9840

0.9826

F score (low traffic)

0.9927

0.9927

0.9927

0.9943

0.9927

F score (mild traffic)

0.9525

0.9584

0.9564

0.9608

0.9564

F score (high traffic)

0.9825

0.9873

0.9855

0.9855

0.9855

Jaccard score (low traffic)

0.9856

0.9856

0.9856

0.9886

0.9856

Jaccard score (mild traffic)

0.9093

0.9203

0.9165

0.9245

0.9165

Jaccard score (high traffic)

0.9657

0.9750

0.9714

0.9714

0.9714

First important predictor

t12

t12 & t16

t0

t0

t12

Second important predictor

t0

t11

t11 & t5

t18

t18