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Data Mining Lab


The Data Mining (DM) Lab aims at helping students to gain hands on experience on data mining by pursuing some DM related project.
At the end of the project you have gone through the whole Knowledge Discovery in Databases (KDD) process, from dataset selection to preparation, mining and interpretation of the data mining results (also called patterns).

Typically we will break down each project into simpler sub-projects, following the steps of the KDD process: 

  • Dataset selection step: acquire/select the data that are relevant for the analysis task
  • Dataset preparation step: cleaning, feature transformation, feature selection,…
  • Data mining step: which data mining task (clustering, classification,…)? Which algorithm? What parameters?
  • Interpretation of the extracted patterns step: what do the data mining results show? 

Depending on the specific project, we might focus more in some of these steps e.g. in dataset preparation or in pattern extraction.

ECTS points: 6


  • Lecture: 
    • Kick-off meeting Thursday, 07.04.2016, 09:00-13:00
    • There are no regular class meetings, only personal meetings to discuss on your project. Please check kick-off meeting slides in Stud-ip. 

  • Room: 

    • Kick-off meeting at  Konferenzraum, EG, Appelstraβe 4.

Teaching team

  • Responsible Professor: Prof. Dr. Eirini Ntoutsi
  • Assistance: To be announced

!!! Please check the Stud.IP page for announcements, material and up-to-date information on the course.