En mycket mer effektiv metod är Euklides algoritm.
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By using the cluster algorithm K-means, and Euclidean distance, which is used as calculation of distances in similar areas, we could then find relevant clusters with deviating data points and key factors with great impact on the bicycle flow.
Genom att använda oss av klusteranalysen K-means och Euklidisk distans som används som beräkning av distanser inom liknande områden kunde vi finna relevanta kluster med avvikande datapunkter och faktorer med stor inverkan på cykelflödet.
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