105.707 Advanced Methods for Regression and Classification
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
Lecture TubeTUWEL

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • LectureTube course
  • 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.

6 October 2022 - 26 January 2023, Thursdays from 11:30 - 12:30

TUWEL

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed08:00 - 10:0005.10.2022 - 11.01.2023HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu11:30 - 12:3006.10.2022 - 26.01.2023 Zoom Link in TUWEL (LIVE)Übung
Wed08:00 - 10:0018.01.2023 - 25.01.2023GM 5 Praktikum HS- TCH Vorlesung Filzmoser
Advanced Methods for Regression and Classification - Single appointments
DayDateTimeLocationDescription
Wed05.10.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu06.10.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed12.10.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu13.10.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed19.10.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu20.10.202211:30 - 12:30 Zoom Link in TUWELÜbung
Thu27.10.202211:30 - 12:30 Zoom Link in TUWELÜbung
Thu03.11.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed09.11.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu10.11.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed16.11.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu17.11.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed23.11.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu24.11.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed30.11.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu01.12.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed07.12.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Wed14.12.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu15.12.202211:30 - 12:30 Zoom Link in TUWELÜbung
Wed21.12.202208:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser

Examination modalities

Solving examples in R, oral exam

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Thu08:30 - 11:0001.12.2022Sem.R. DA grün 06B written&oral25.10.2022 12:00 - 29.11.2022 23:59TISSOral Presence Exam AMRC
Mon09:00 - 13:0009.01.2023Sem.R. DA grün 02 C written&oral24.11.2022 12:00 - 07.01.2023 23:59TISSOral Presence Exam AMRC

Course registration

Begin End Deregistration end
01.09.2022 09:00 16.10.2022 12:00 16.10.2022 12:00

Curricula

Literature

No lecture notes are available.

Miscellaneous

Language

English