Data Mining : Artificial intelligence
Overview
Achievment: SWS : 2, Credits 4
Course type: lecture
Language: english
Exam date: 27.07.2012
Second exam date :
Material
All material can be found in ILIAS
Content
Special data mining methods in the area of soft computing and artificial intelligence.
- Introduction to Fuzzy Logic
- Learning from Fuzzy Logic Models
- Introduction to Neural Networks
- Learning and Analysis of Neural Networks
- Introduction to Metaheuristics
- Evolution of rule- and other Models
- Hybrid Methods of Soft Computing in Data Mining
Literature
For the lecture:
- For all topics: Michael Berthold, David Hand: Intelligent Data Analysis, An Introduction, 2te Auflage, Springer-Verlag, 2003.
- Online book Fuzzy Logic (deutsch) partly very theoretical
- Book about neuronal networks (and fuzzy systems) (german): Detlef Nauck, Christian Borgelt, Frank Klawonn und Rudolf Kruse.: Neuro-Fuzzy-Systeme - Von den Grundlagen Neuronaler Netze zu modernen Fuzzy-Systemen Vieweg-Verlag, Wiesbaden, Germany 2003, ISBN 3-528-25265-0
- Very detailed slide based script by Christian Borgelt "Introduction to Neural Networks"
- Another script to neuronal networks (german) Ein kleiner Überblick über Neuronale Netzwerke
Basics for Data Mining :
- Berthold, Borgelt, Höppner, Klawonn: Guide to Intelligent Data Analysis, Springer 2011
- Tom Mitchell: Machine Learning, McGraw Hill, 1997
- David Hand, Heikki Mannila, Padhraic Smyth: Principles of Data Mining, MIT Press 2001
Course criteria
Active participation in the exercise: vote for at least 60% of the exercise, that is to agree to show the solution approach on the black board.
Oral (30 minutes) exam.
The final mark is the mark of the exam
Prerequisites
Basic knowledge within the content of the Data Mining 1 lecture repectively the book Guide to Intelligent Data Analysis is advantageous.
