The last 1 point of the last k points is the destination, use the same values as the features and the labels, is this rational??

[wongprince]

First, thanks for sharing your amazing work! I have a question and hope to get reply from you. “we chose to consider only the first k points and last k points of the trajectory prefix, which gives us a total of 2k points, or 4k numerical values for our input vector. For the winning model we took k = 5.” In this case, the last 1 point of the last 5 points is the destination/target, the neural net will learn to establish a strong relationship between the target and the last 1 point (2 features: latitude and longitude), regardless of other features. Right? And in the test dataset, the last 1 point is not the real destination, cause the trip is not finished. Why you could get a good results? I just can’t understand this, and could you explain for me?

Looking forward your reply, thanks in advance.