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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