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Tree insight: a path toward Data Science for all

profilePhoto   Numa Schenone
Linksium Contact Numa Schenone +33 (0)7 78 09 11 94


  • Giving users back control of the data analysis process
  • Shorten and refocus the decision-making chain
  • Interactively visualize and explore up to one million observations in real time

Key words

  • Data analysis
  • Graphical interface
  • Clustering and decision Trees
  • Human Computer Interface

Intellectual Property

  • 1 software


  • LIG


  • CNRS
  • UGA

Linksium Continuum

  • Maturation
  • Incubation


Treensight is a generic and extensible graphical user interface that allows interactive visualization and manipulation of clustering and decision trees with keeping a tight link with the data. Treensight ensures an efficient collaboration user/machine by offering a better control on the analyzed data and a detailed insight into each cluster.


Treensight is a multiplatform application (macOS, Linux, Windows). It has three components:

  • The Core (Javascript): it proposes visualization, filtering and exploration technique up to 1M data.
  • An extensible library of scripts (Python): implementation of Machine Learning, analysis and manipulation functions.
  • Communication protocole: ensures the link between the Core and the library of scripts.


Treensight has four main features:

  • Dynamic content: information about the selected cluster is displayed in the right-hand panel: name, statistics about the instances, distances, etc.
  • Instances repartition: the left-hand panel allows the creation of « View points ». In each one the user selects coloring rules and visualization modes that will be displayed in the central panel.
  • Variables comparison: user can compare the statistics of a variable coming from different clusters.
  • Clusters comparison: in the same fashion, user can compare the clusters and their evolution.

State of progress

A first cross-platform (Windows, Linus, MacOS) version of the software is released, with restricted access. This software is used in several projects by researchers from various disciplines.


  • Science and technology: classification, research of indicators, maintenance...
  • Medical and health field: cohort analysis, sensitivity/specificity study...
  • Marketing and economy: impact of a campaign, user profiling...
  • Sociology: study of populations and their evolution, analysis of surveys...

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