Monographic lecture - Combinatorial machine learning Field of study: Computer Science
Programme code: W4-N2IN19.2021

Module name: Monographic lecture - Combinatorial machine learning
Module code: W4-IN-N2-20-2-WMwJA
Programme code: W4-N2IN19.2021
Semester:
  • summer semester 2022/2023
  • winter semester 2022/2023
Language of instruction: English
Form of verification: course work
ECTS credits: 2
Description:
The aim is to acquaint students with decision trees, decision rules and tests as tools for discovering knowledge from data, their analysis, study relationships between these objects, and show examples of applications.
Prerequisites:
(no information given)
Key reading:
1. Moshkov M., Zielosko B.: Combinatorial Machine Learning - A Rough Set Approach. Studies in Computational Intelligence 360, Springer 2011, ISBN 978-3-642-20994-9 2. Han J., Kamber M.: Data Mining: Concepts and Techniques, Morgan Kaufmann 2011 3. Pawlak Z., Skowron A.: Rudiments of rough sets. Inf. Sci. 177(1): 3-27 (2007)
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]
Can recognize analogies in the knowledge presented in the lecture, as well as the concepts employed out in other courses. [M_001]
 K_W02 [2/5] K_U01 [4/5]
Knows what are the decision rules, decision trees and reducts, and can provide examples of their application to solve real problems. [M_002]
 K_W09 [3/5] K_U07 [4/5]
Is able to present an algorithm for construction decision rules, decision trees and tests. [M_003]
 K_W02 [3/5] K_W04 [1/5]
Is able to present the problem of construction rules, trees and tests as an optimization problem. [M_004]
 K_W02 [2/5] K_U08 [2/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Test [W_001]
Knowledge verification is based on the content presented during lectures.
 M_001 M_002 M_003 M_004
Solving assignments [W_002]
Presentation, in specified term, results of solved assignments as a verification of skills acquired during problem solving.
 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]
Forwarding knowledge in verbal form using audio-visual media and other written didactic aids. Paying attention to issues more difficult to understand. Activation of students by asking questions and simple tasks regarding the considered topic.
 20
Familiarize students with the subject of lectures, investigation discussed issues in the framework of connections between the examined objects, solving tasks in the area of knowledge presented during lectures.
 40 Test [W_001] Solving assignments [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)