• Real Time Clustering

  • Profile discovering

    Profile discovering or cluster analysis is a very common technique for statistical data analysis. Its main goal is to group together objects, people, or complex systems being the most similar. It is used in many fields such as marketing, e-commerce, bioinformatics, medecine, image analysis, pattern recognition and so one.

    The Profile Discovering algorithm developed by LumenAI performs a fully data-driven clustering procedure. It maintains for each new event, object, or person the best partition of data in real time. One of its main asset is that the number of segments (or clusters) is managed automatically. It means that the partition is automatically adapted each time a new event appears and therefore the segmentation of your data is updated in real-time: new behaviors or moving behaviors are therefore detected.

    Toy example

    What is "resolution"?

    As we are aware that the classification is a relative issue, you can change the resolution to tell us if you need more or less clusters.

    Generate some random data

    How?

    Click on the grid below to generate your data and our algorithm will classify the stream you will create in order to get the optimal classification based on your data distribution.

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