Methods of group decision making Field of study: Computer Science
Programme code: W4-S2IN19.2022

Module name: Methods of group decision making
Module code: W4-IN-S2-20-F-MPDG
Programme code: W4-S2IN19.2022
Semester:
  • summer semester 2025/2026
  • winter semester 2025/2026
  • summer semester 2024/2025
  • winter semester 2024/2025
  • summer semester 2023/2024
  • winter semester 2023/2024
Language of instruction: Polish
Form of verification: course work
ECTS credits: 4
Description:
The course aims to present issues related to multiple classifier system and fusion methods used when making group decisions. The subject will also cover selected issues from game theory. Content: 1. Topology and architecture of multiple classifier system 2. Methods of constructing combined classifiers: Bagging, Boosting, methods of selecting variables 3. Methods for combining prediction results of base classifiers: fusion methods from the abstract, rank and measurement levels 4. The problem of diversity of base models 5. Introduction to the two-player games, payoff matrix and the Nash equilibrium 6. Introduction to the n-player games and the Shapley value
Prerequisites:
(no information given)
Key reading:
1. Lidmila I. Kunchewa,Combining Pattern Classifiers, Methods and Algorithms, JohnWiley & Sons, Inc., Hoboken, New Jersey 2004 2. Philip D. Straffin, Game Theory and Strategy (New Mathematical Library, No. 36), 1993
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
The student has knowledge about the topology and architecture of multiple classifier system, methods of building combined classifiers and techniques for fusion of based models' predictions. [M_001]
 K_W02 [1/5] K_W05 [2/5] K_W09 [1/5]
The student has knowledge of the basic issues related to two-player and n-player games i.e. the payoff matrix, the Nash equilibrium and the Shapley value. [M_002]
 K_W01 [1/5]
She/He can choice appropriate architecture and topology of multiple classifier system to the considerad problem. She/He can carry out the process of building a combined classifiers and apply the appropriate fusion method. [M_003]
 K_U03 [1/5] K_U08 [1/5] K_U09 [1/5]
She/He can use the selected program to perform the analysis using multiple classifier system. [M_004]
 K_U09 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Examination reports [W_001]
Preparation of written reports and their oral presentation at a specified time as a verification of acquired skills during problems' solving.
 M_001 M_002 M_003 M_004
Test [W_002]
Verification of knowledge and skills based on the analysis of tasks solutions during written test.
 M_001 M_002 M_003
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
Lecture presenting concepts and facts from the scope of program contents which are listed in the module and illustrating them with numerous examples
 15
Self-study of lectures and literature
 15 Test [W_002]
laboratory classes [Z_002]
Laboratory, during which students perform exercises with the help of the teacher, which develop the skills listed in the set of learning outcomes of the module
 30
Self-improvement of skills listed in the set of learning outcomes of the module
 60 Examination reports [W_001] Test [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)