Data Mining and Knowledge Discovery

professor: prof. Nada Lavrač

professor: dr. Petra Kralj Novak

professor: prof. Bojan Cestnik

professor: dr. Martin Žnidaršič

Courses

• Information and Communication Technologies (ICT2): Data and Text Mining / Podatkovno in tekstovno rudarjenje (20 ECTS)
• Information and Communication Technologies (ICT3): Data Mining and Knowledge Discovery / Podatkovno rudarjenje in odkrivanje zakonitosti (10 ECTS)
• Statistics PhD program: Podatkovno rudarjenje in odkrivanje zakonitosti v podatkih (5 kt)

Scheduled lectures and course materials in school year 2018/19

Materials:

• Bojan Cestnik (ICT2): Data and text mining
• Nada Lavrac: Lecture notes
• Martin Žnidaršič: Lecture notes

Practice materials: dr. Petra Kralj Novak

• Practice notes:
• 8.11.2018 Classification I
• Slides (.pdf) , 6/page (.pdf)
• Entropy and information gain (.pdf)
• Decision trees (.pdf)
• 15.11.2018 Classification II
• Slides - Part 1: (.pdf) , 6/page (.pdf)
• Slides - Part 2: (.pdf) , 6/page (.pdf)
• Naive Bayes (.pdf)
• 29.11.2018 Numeric prediction and Association rules
• Slides (.pdf) , 6/page (.pdf)
• Association rules (.pdf)
• 6.12.2018 Clustering
• Slides (.pdf) , 6/page (.pdf)
• Hands on Weka
• Hands on Weka Part 1 (.pdf), 6/page (.pdf)
• Hands on Weka Part 2 (.pdf), 6/page (.pdf)
• Hands on Weka Part 3 (.pdf), 6/page (.pdf)
• datasets (.zip)
• Hands on Scikit-learn: numeric prediction and clustering and gitlab repository
• Intoduction to Deep learning (.pdf), 6/page (.pdf) gitlab repository

Book club:

1. Max Bramer: Principles of Data Mining (2007)
   • We will study the book: Max Bramer: Principles of Data Mining (2007) and discuss it in three sessions
   • Chapters 1-5
   • Chapters 6-10
   • Chapters 11-15

Course requirements ICT2, data mining part:

• Attending lectures
• Attending practical exercises : Theory exercises and hands-on (intro to WEKA by Petra Kralj Novak)
• Collaborating in the book club
• Written exam
• Seminar: half page proposal, 4 pages written report, oral presentation, all in English
1. Written exam
   • 60 minutes of time
   • 4 tasks: 2 computational (60%), 2 theoretical (40%)
   • Literature is not allowed
   • Each student can bring one hand-written A4 sheet of paper and a hand calculator
2. Data mining seminar
   • Half page seminar proposal on written exam day
   • Data analysis of your own data (Weka recommended)
   • Deliver a 4 pages written report (printed and electronic copy) in Information Society paper format
     on seminar presentations day (use paper template and guidelines)
   • Oral presentation of seminar results (10 minutes for presentation + 5 minutes discussion, use slides template)

Course requirements ICT3

• Attending lectures
• Collaborating in the book club
• Written exam
• Seminar: written part, oral presentation, both in English

1. Written exam
   • 60 minutes of time
   • 4 tasks: 2 computational (60%), 2 theoretical (40%)
   • Literature is not allowed
   • Each student can bring one hand-written A4 sheet of paper and a hand calculator
2. Data mining seminar from advanced data mining topics
   • Data analysis of your own data in Clowdflows or by using other data mining toolboxes
   • One page seminar proposal on written exam day
   • Deliver a 4 pages written report (printed and electronic copy) in Information Society paper format
     on seminar presentations day (use paper template and guidelines)
   • Oral presentation of seminar results (10 minutes for presentation + 5 minutes discussion, use slides template)

Examples of data mining seminars:

• Janez Bucik (.pdf)
  Microsoft stock quotes dependency analysis
• 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:
   • Statistični urad Republike Slovenije
   • Ljubljanska borza d.d.
   • Banka Slovenije
   • World Health Organization
   • Center for Climatic Research, University of Delaware

Templates

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

Useful links

• Weka
• ClowdFlows

Link to last year's web page - Data Mining and Knowledge Discovery 2017/2018
Last update: 20190110