Question

I have a multi-layer neural network based estimator that takes inputs the past arrival times of vehicles and estimates the arrival time of next vehicle (with a backpropagation algorithm). Based on a certain threshold (e.g, 10sec), the estimator classifies the predicted time to be high or low (1 or 0). My problem is that, based on the observed and predicted/estimated arrival times (1’s & 0’s), how do I calculate the accuracy (or the correct prediction rate) of the overall prediction?

Answer 1

You will have to define for yourself what you mean with high (1) and low (0). For example, you could say that high arrival time equals 5 minutes or more, and low arrival time as less than 5 minutes. Once your neural network gives a prediction, then you can check in your samples whether the next car’s arrival time is indeed high or low (i.e., respectively more than 5 minutes or less than 5 minutes). You can calculate the accuracy of your prediction using this.