Decision and association rules in knowledge data discovery Field of study: Computer Science
Programme code: W4-S2INA19.2021

Module name: Decision and association rules in knowledge data discovery
Module code: W4-INA-S2-20-F-RDAOW
Programme code: W4-S2INA19.2021
Semester:
  • summer semester 2022/2023
  • winter semester 2022/2023
  • summer semester 2021/2022
Language of instruction: English
Form of verification: course work
ECTS credits: 4
Description:
The module aims at acquainting the students with decision and association rules as models of knowledge representation and classification. The students learn about rule quality measures and approaches and algorithms for their construction and knowledge discovery applications.
Prerequisites:
(no information given)
Key reading:
1. Han J., Kamber M.: Data Mining: Concepts and Techniques, Morgan Kaufmann 2011 2. Cichosz P.: Systemy uczące się, WNT 2009 3. Krawiec K., Stefanowski J.: Uczenie maszynowe i sieci neuronowe, Wydawnictwo Politechniki Poznańskiej 2003 4. Larose D.: Metody i modele eksploracji danych, PWN 2008
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 knows quality measures for knowledge representation as decision and association rules. [M_001]
 K_W09 [3/5]
The student knows approaches and algorithms for construction decision and association rules. [M_002]
 K_W02 [3/5] K_W04 [2/5]
The student can apply decision and association rules in knowledge discovery. [M_003]
 K_W09 [3/5] K_U01 [4/5] K_U03 [4/5] K_U08 [3/5]
The student can choose and present the algorithm for creating a classification model for the considered problem. [M_004]
 K_U08 [3/5] K_U09 [3/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Test [W_001]
The students prepare and present reports in the specified deadline to verify skills gained while completing laboratory assignments.
 M_001 M_002 M_003
Raport presentation for laboratory tasks [W_002]
The students prepare and present reports in specified deadline as a verification of skills acquired during completing laboratory assignments.
 M_001 M_002 M_003 M_004
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]
The lectures have a verbal form using audiovisual media and other written teaching aids. The students are encouraged by asking questions and simple tasks regarding the considered topics.
 15
The students get acquainted with the subject of lectures and investigate considered topics.
 15 Test [W_001]
laboratory classes [Z_002]
The classes prepare students for solving problems and complete assignments, emphasising the method and operations sequence.
 30
The students study for laboratory classes, complete laboratory tasks and prepare reports.
 60 Raport presentation for laboratory tasks [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)