recently, I have been working on track data clustering. Now I have track data of about 2 million people on hand. Each person"s track consists of a sequence of points (a point position every half hour), as shown in the table
. A day is divided into 48 intervals, each of which is half an hour
for this large-scale trajectory data clustering, I extracted part of the data and tried the Scipy hierarchical clustering that comes with Python. But if the amount of data is too large, how to deal with it? I don"t know if you have any experience to tell me. Thank you!
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