Data Mining

Teaching personnel


Lecturer

Formalia


Targeted audience
  • DAI Hauptstudium with 4 credit points : Bereich "D"
  • ISE Master with 4 credit points

Dates


Lectures

Date

Time

Place

Mittwoch 14:15 - 15:45LF/052

Description


Data mining deals with the extraction of implicit, yet unknown knowledge from raw data. For this purpose, there are methods for analyzing databases, in order to identify patterns and to perform abstraction, in order to produce valuable knowledge. The methods applied are based on machine techniques.

Lecture material


The course is based on the book `Data Mining' by Ian Witten und Eibe Frank

Course structure:


  1. Input: Concepts, Instances, Attributes
  2. Output: Knowledge Representation
  3. Algorithms: The Basic Methods
  4. Credibility: Evaluating What's Been Learned
  5. Implementations: Real Machine Learning Schemes
  6. Moving On: Engineering the Input and Output
  7. Nuts And Bolts: Machine Learning Algorithms In Java

Slides


The slides and other background material can be found here.

Assignments / preparation for the oral exam