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Traffic prediction is a multi-step prediction problem, and a common scheme is to predict the future 12 steps based on the historical 12 steps.
There are 2 evaluation methods for multistep forecasting, (1) reporting the average results of multiple steps and (2) reporting the results of each step individually. These two methods have been used extensively in past articles.
In LibCity you can choose between these two methods by setting the evaluation mode.
For (1) you need to set "mode": "average", assuming that there are 12 steps of prediction, in this mode, the 12 results obtained are average results, that is, the result in line 12 is the average result of the first 12 steps, line 11 is the average result of the first 11 steps, and so on, and line 1 is the average result of the first 1 step.
For (2) you need to set "mode": "single", assuming that there are 12 steps in the prediction, in this mode the 12 results obtained are the results of each step individually, i.e., the result in line 12 is the result of step 12, line 11 is the result of step 11, and so on, and line 1 is the result of step 1.
This parameter is configured in the file libcity/config/evaluator/TrafficStateEvaluator.json.
Results in average mode are usually better than in single mode because multi-step predictions usually have worse results at more distant time steps, so multi-step averaging is better than results for each step individually.
The text was updated successfully, but these errors were encountered:
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How to set the evaluation mode for traffic prediction?
How to set the evaluation mode for traffic prediction? single or average
Oct 5, 2023
Traffic prediction is a multi-step prediction problem, and a common scheme is to predict the future 12 steps based on the historical 12 steps.
There are 2 evaluation methods for multistep forecasting, (1) reporting the average results of multiple steps and (2) reporting the results of each step individually. These two methods have been used extensively in past articles.
In LibCity you can choose between these two methods by setting the evaluation mode.
For (1) you need to set "mode": "average", assuming that there are 12 steps of prediction, in this mode, the 12 results obtained are average results, that is, the result in line 12 is the average result of the first 12 steps, line 11 is the average result of the first 11 steps, and so on, and line 1 is the average result of the first 1 step.
For (2) you need to set "mode": "single", assuming that there are 12 steps in the prediction, in this mode the 12 results obtained are the results of each step individually, i.e., the result in line 12 is the result of step 12, line 11 is the result of step 11, and so on, and line 1 is the result of step 1.
This parameter is configured in the file libcity/config/evaluator/TrafficStateEvaluator.json.
Results in average mode are usually better than in single mode because multi-step predictions usually have worse results at more distant time steps, so multi-step averaging is better than results for each step individually.
The text was updated successfully, but these errors were encountered: