DBSCAN is a powerful clustering algorithm used in various machine learning applications. A wide range of research has focused on clustering geographical Points Of Interest (POI), in an unsupervised way. Most of the existing approaches use DBSCAN coordinates as input but do not include other features in the clustering process.

In this article, we introduce a multi-feature model to geo clustering with DBSCAN allowing for more features than the sole location. We present an example of an application suggesting that this approach can in some cases perform better.

How DBSCAN works

How DBSCAN works — from Wikipedia

DBSCAN stands for Density-Based Spatial Clustering of Applications with Noise. It is…


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“Data Science”, c’est un terme de plus en plus populaire et qui tend à devenir un maître mot pour désigner beaucoup de domaines scientifiques et du domaine de l’ingénieur : Big Data, Intelligence Artificielle, Graphes et Réseaux, Data mining, Statistiques… Mais concrètement, pourquoi serait-ce nécessaire de s’y intéresser et quel avenir nous réservent les données ?

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300%, c’est…

Sylvain Marchienne

Machine Learning Engineer

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