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I am working with a dataset where each record is a certain type of trip. For example, one record would have the data points:

  • number of days of trip
  • day the trip started
  • where the trip started
  • how many hours the trip was
  • how many times stops occurred on each trip

What I'm trying to approximate is how similar these trips actually are if they are similar. Or how different are they? Ideally, I can come up with 5 features of the dataset that each instance in the original dataframe all have in common.

I assume that some sort of clustering method should be used, but I am new to clustering. If I could get pointed in any direction to understand which algorithm I should be investigating, that would be much appreciated!!

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Assuming all the 5 features are numerical, clustering algorithm could be deployed. Apart from that, cosine similarity between the individual vectors, where each vector would represent a trip.

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