University of Pardubice
Study programmes & Course catalogue
for academic year 2016/2017
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Course: Methods and Data Mining Algorithms

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Course title Methods and Data Mining Algorithms
Course code FES/DMAD
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 10
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Petr Pavel, doc. Ing. Ph.D.
  • Skalská Hana, prof. RNDr. CSc.
Course content
unspecified

Learning activities and teaching methods
unspecified
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
unspecified
Recommended literature
  • Berka, Petr. Dobývání znalostí z databází. Praha: Academia, 2003. ISBN 80-200-1062-9.
  • BERRY, M. - LINOFF G. Data Mining Techniques - For Marketing, Sales, and Customer Relationship Management. Indianapolis, John Wiley & Sons, 2004, 643 s.. 2004.
  • Feldman. The text mining handbook : advanced approaches in analyzing unstructured data. New York, 2007.
  • Giudici, Paolo. Applied data mining : statistic methods for business and industry. Chichester: Wiley, 2003. ISBN 0-470-84678-X.
  • larose. Data mining methods and models. 2006.
  • Maimon. Decomposition methodology for knowledge discovery and data mining: theory and application. Singapure, 2005.
  • Tsiptsis, Konstantinos. Data mining techniques in CRM : inside customer segmentation. Chichester: John Wiley & Sons, 2009. ISBN 978-0-470-74397-3.
  • WITTEN, I.H., FRANK, E., HALL, M.A. Data Mining: Practical Machine Learning Tools and Techniques. Amsterdam, 2011.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2014) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2013) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2013) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2014) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
University of Pardubice, date of update: 22.07.2024 23:50. Data created for academic year 2016/2017