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Jožef Stefan International Postgraduate School
Statistics
2011/2012
Data Mining Courses Webpage
Courses:
Jožef Stefan IPS MSc (ICT2/IKT2):
(A) Data Mining and Knowledge Discovery / Podatkovno rudarjenje in odkrivanje zakonitosti (8/24 ct)
Jožef Stefan IPS PhD (ICT3/IKT3) Module Knowledge Technologies / Modul Tehnologije znanja:
(B) Selected techniques for tabular and relational data mining / Izbrane tehnike rudarjenja tabelaričh in večrelacijskih podatkov (3 ct)
Statistics MSc program:
(C) Data mining / Podatkovno rudarjenje (5 ct)

Wednesday, 26. 10. 2011 15:15 - 17:00
Seminar I (ICT3): Knowledge Technologies - Data Mining
(prof. dr. Nada Lavrač)
IPS lecture hall
17:15 - 19:00
Selected techniques for tabular and relational data mining (ICT3)
(prof. dr. Nada Lavrač)
IPS lecture hall
Tuesday, 8. 11. 2011 17:15 - 19:00 Practice
(dr. Petra Kralj Novak)
IPS lecture hall
Tuesday, 15. 11. 2011
17:15 - 19:00 Data Mining and Knowledge Discovery (ICT2)
(N. Lavrač, B. Cestnik, D. Mladenić, P. Kralj Novak)
IPS lecture hall
Tuesday, 22. 11. 2011 17:15 - 19:00 Practice
(dr. Petra Kralj Novak)
IPS lecture hall
Tuesday, 29. 11. 2011 17:15 - 19:00 Practice
(dr. Petra Kralj Novak)
IPS lecture hall
? ?
Statistika - Sodobni statistični pristopi - rudarjenje podatkov
(prof. dr. Nada Lavrač)
?
Tuesday, 20. 12. 2011 17:00 - 18:00 Data Mining written exam
(dr. Petra Kralj Novak)
IPS lecture hall
18:00 - 19:00 Data Mining seminar topic presentations
(dr. Petra Kralj Novak)
IPS lecture hall
Tuesday, 24. 1. 2012 17:15 - 19:00 Data mining seminar presentations
(prof. dr. Nada Lavrač, dr. Petra Kralj Novak)
IPS lecture hall

Course materials

  • page of the part of the DATA MINING AND KNOWLEDGE DISCOVERY (ICT2) course on data preprocessing that is covered by doc. dr. Bojan Cestnik
  • Lectures: prof. dr. Nada Lavrač
    • lecture notes: to appear
  • Practice: dr. Petra Kralj Novak
    • practice notes:
      • 8.11.2011 slides: (.pdf) , 6/page (.pdf);
      • entropy and information gain (.pdf)
      • decision trees (.pdf)
      • 22.11.2011 slides: (.pdf) , 6/page (.pdf);
      • naive Bayes (.pdf)
      • 29.11.2011 slides: (.pdf) , 6/page (.pdf)
      • association rules (.pdf)
    • hands on Weka
      • classification (.pdf), 6/page (.pdf)
      • numeric prediction (.pdf), 6/page (.pdf)
      • classificarion and association rules (.pdf), 6/page (.pdf)
      • datasets (.zip)

Useful links

Course requirements:

Students Jožef Stefan IPS MSc (ICT2) course Data Mining and Knowledge Discovery (8/24 ct): written exam and seminar
Jožef Stefan IPS PhD (ICT3) course Selected techniques for tabular and relational data mining (3 ct): written exam
Statistics Phd program course Data mining (5 ct): written exam and seminar

  1. Written exam
    • 45 minutes of time
    • 4 tasks (2 computational, 2 theoretical)
    • Literature is not allowed
    • Each student can bring one hand-written A4 sheet of paper and a hand calculator
  2. Data mining seminar
  3. Examples of data mining seminars:

    • Janez Bucik (.pdf)
      Microsoft stock quotes dependency analysis
    • Matej Gašperin (.pdf)
      Case study on the use of data minig techniques in food science using honey samples
    • Valentin Koblar (in Slovene .pdf)
      Napoved menjalnega tečaja ameriškega dolarja na podlagi menjalnih tečajev tujih valut

    Ideas for seminars

    1. Analyze some data where you are the domain expert, use at least two algorithms
    2. Find some interesting data to analyze, possible sources:

    Templates

    • presentation template (.pot)
    • paper template (.doc)
    • paper guidelines (.doc)

    Link to last year's web page - Data Mining and Knowledge Discovery 2010/2011
Last update: 20111130