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.

2022W, 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 the 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. The many topics include neural networks, support vector machines, classification trees and generalized additive models.

Teaching methods

Examples with data, software environment R

Mode of examination

Written and oral

Additional information

The practice part takes place online. The other part will be held in the following rooms: Wednesday, 5 October 2022 - 11 January 2023, 8:00 - 10:00, HS 17 Friedrich Hartmann and from 18 January 2023 in GM 5 Praktikumshörsaal.

Detailed information under VU 105.707.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed08:00 - 10:0005.10.2022 - 25.01.2023 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu11:30 - 12:3006.10.2022 - 26.01.2023 Zoom-Link in TUWEL (LIVE)Übung Filzmoser
Classification and Discriminant Analysis - Single appointments
DayDateTimeLocationDescription
Wed05.10.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu06.10.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed12.10.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu13.10.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed19.10.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu20.10.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Thu27.10.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Thu03.11.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed09.11.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu10.11.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed16.11.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu17.11.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed23.11.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu24.11.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed30.11.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu01.12.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed07.12.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Wed14.12.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser
Thu15.12.202211:30 - 12:30 Zoom-Link in TUWELÜbung Filzmoser
Wed21.12.202208:00 - 10:00 05.10.2022-11.01.2023, HS 17 Friedrich Hartmann, ab 18.01.2023, GM 5Vorlesung Filzmoser

Examination modalities

Solving examples in R, oral exam

Course registration

Begin End Deregistration end
19.09.2022 12:00 16.10.2022 12:00 16.10.2022 12:00

Curricula

Literature

Lecture notes for this course are available from the lecturer.

Miscellaneous

  • Attendance Required!

Language

German