PřF:M8DM1 Data mining I - Course Information
M8DM1 Data mining I
Faculty of ScienceSpring 2012
- Extent and Intensity
- 2/2/0. 4 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Martin Řezáč, Ph.D. (lecturer)
Mgr. Bc. Jan Kovář (seminar tutor) - Guaranteed by
- Mgr. Martin Řezáč, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Thu 12:00–13:50 M1,01017
- Timetable of Seminar Groups:
M8DM1/02: Thu 16:00–17:50 MP2,01014a, J. Kovář
M8DM1/03: Fri 10:00–11:50 MP2,01014a, M. Řezáč
M8DM1/04: Thu 18:00–19:50 MP2,01014a, J. Kovář - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Financial and Insurance Mathematics (programme PřF, B-AM)
- Financial and Insurance Mathematics (programme PřF, B-MA)
- Finance Mathematics (programme PřF, N-AM)
- Finance Mathematics (programme PřF, N-MA)
- Course objectives
- Data mining is a proven way how to get best knowledge from data for decision making. The course is an introduction to data mining issues, definitions of basic concepts, an introduction and practice of the methods and techniques that are used in practice. Students will gain a basic knowledge of these methods, which they will deepen in the computer exercises using SAS system.
- Syllabus
- History of data mining, basic concepts, software.
- Data organization, itroduction to SQL.
- Data preparation.
- SAS data step.
- Exploratory analysis, visualization, kontingency tables.
- Logistic regression.
- Decision trees.
- Neural networks.
- Evaluation of given model – LC (ROC), Gini, KS, Lift.
- Literature
- GIUDICI, Paolo. Applied data mining : statistical methods for business and industry. Chichester: Wiley, 2003, xii, 364. ISBN 0470846798. info
- THOMAS, L. C., David B. EDELMAN and Jonathan N. CROOK. Credit scoring and its applications. Philadelphia, Pa.: Society for Industrial and Applied Mathematics, 2002, xiv, 248. ISBN 0898714834. URL info
- SIDDIQI, Naeem. Credit risk scorecards : developing and implementing intelligent credit scoring. Hoboken, N.J.: Wiley, 2006, xi, 196. ISBN 047175451X. info
- THOMAS, L. C. Consumer credit models : pricing, profit, and portfolios. 1st pub. Oxford: Oxford University Press, 2009, xii, 385. ISBN 9780199232130. info
- Teaching methods
- Lectures and exercises.
- Assessment methods
- project in SAS, oral exam
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Enrolment Statistics (Spring 2012, recent)
- Permalink: https://is.muni.cz/course/sci/spring2012/M8DM1