Monographic lecture - Combinatorial machine learning Field of study: Computer Science
Programme code: W4-S2INA19.2021

Module name: Monographic lecture - Combinatorial machine learning
Module code: W4-INA-S2-20-2-WMwJA
Programme code: W4-S2INA19.2021
Semester: 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. Subsequently, the students will analyse them, study relationships between these objects, and show examples of their 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]
The student can recognise analogies in the knowledge presented in the lecture and the concepts employed out in other courses. [M_001]
 K_W02 [2/5] K_U01 [4/5]
The student knows the decision rules, decision trees and reducts, and can provide examples of their application to solving real problems. [M_002]
 K_W09 [3/5] K_U07 [4/5]
The student can present an algorithm for construction decision rules, decision trees, and tests. [M_003]
 K_W02 [3/5] K_W04 [1/5]
The student can present the problem of construction rules, trees, and tests as an optimisation 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]
The test verifies the knowledge presented during the lectures.
 M_001 M_002 M_003 M_004
Completing assignments [W_002]
The students present, in the specified term, results of completed assignments as verification of skills.
 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 audio-visual media and other written teaching aids, emphasising issues more difficult to understand. The students are encouraged by asking them questions and giving them simple tasks regarding the considered topic.
 30
The students get acquainted with the lectures, analyse the discussed content for the links between the studied objects, and complete the tasks related to the lectures.
 30 Test [W_001] Completing 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)