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Data Science: New Data, New Paradigms

From data to classes and classes as statistical units

Recherche - Formation: Université Paris-Dauphine
22-23 January 2018, Room A707 at 7th floor.

Registration free but obligatory (number of places is limited).
Participation gratuite à condition d’être inscrit car le nombre de places est limité.
Registration at: datascience22230118@gmail.com

A “Data Scientist” is someone who is able to extract knew knowledge from Standard, Big and Complex Data: unstructured data, unpaired samples, multi sources data (as mixture of numerical, textual, image, social networks data). The fusion of such data can be done into classes of row statistical units which are considered as new statistical units. Classes can be obtained by unsupervised learning which give a concise and structured view on the data or by supervised learning in order to produce efficient rules (deep learning). A third way is to consider classes as new statistical units by vectors of intervals, probability distributions, weighted sequences, functions, and the like, in order to express the within-class variability. One of the advantage of this approach is that unstructured data and unpaired samples at the level of row units, become structured and paired at the level of classes.
... more in French


  • Fundamental theory Classes and Symbolic Data
  • Linear Models of symbolic data
  • Clustering for distributional data
  • Symbolic network
  • Dimensional reduction
  • Applications in socio-demography and ecology


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sda/meet/pa18.txt · Last modified: 2018/01/25 17:49 by vlado
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