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107.386 Classification and Discriminant Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, VU, 3.0h, 4.5EC

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to

  • explain and formulate theoretical concepts of important dimension reduction techniques and methods for linear and nonlinear regression and classification
  • identify the strengths and weaknesses of the different statistical methods and tools and to use them in practice

Subject of course

During the past decade there has been an explosion in computation and information technology. With it has come vast amount of data in a variety of fields such as medicine, finance and marketing. The challange to understand these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning and bioinformatics. This lecture describes the important ideas in these areas in a common conceptual framework.

Teaching methods

Examples with data, software environment R

Mode of examination

Written and oral

Additional information

The practice part of this VU will be held online via zoom.

12.10.2023 - 25.01.2024, 11:30-12:30

Detailed information under VU 105.707.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed08:00 - 10:0004.10.2023 - 24.01.2024 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu11:30 - 12:3012.10.2023 - 25.01.2024 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Classification and Discriminant Analysis - Single appointments
DayDateTimeLocationDescription
Wed04.10.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Wed11.10.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu12.10.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed18.10.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu19.10.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed25.10.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Wed08.11.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu09.11.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Thu16.11.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed22.11.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu23.11.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed29.11.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu30.11.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed06.12.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu07.12.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed13.12.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu14.12.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed20.12.202308:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser
Thu21.12.202311:30 - 12:30 Zoom-Link in TUWEL-Course 105.707Übung Filzmoser
Wed10.01.202408:00 - 10:00 HS 17 Friedrich HartmannVorlesung Filzmoser

Examination modalities

Solving examples in R, oral exam

Course registration

Begin End Deregistration end
18.09.2023 12:00 15.10.2023 12:00 15.10.2023 12:00

Curricula

Study CodeObligationSemesterPrecon.Info
066 926 Business Informatics Mandatory elective
066 936 Medical Informatics Mandatory elective
860 GW Optional Courses - Technical Mathematics Not specified

Literature

Lecture notes for this course are available from the lecturer.

Miscellaneous

  • Attendance Required!

Language

German