Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Data Mining Techniques

    A tantárgy neve magyarul / Name of the subject in Hungarian: Adatbányászati technikák

    Last updated: 2012. november 24.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics
    Course ID Semester Assessment Credit Tantárgyfélév
    VISZM185 1,3 3/1/0/f 5  
    3. Course coordinator and department Dr. Pintér Márta,
    8. Synopsis The course is concerned with the essential tools and concepts of data mining. In the course of laboratory practices the students get acquainted with the application of the most widespread data mining software packages. The syllabus includes the following areas: General introduction to data mining. Pre-processing, data-transformation, similarity measures. Frequent set search. Association rules. Feature indicators.
    Classification, nearest neighbor method, decision rules, decision trees. Clustering, classical clustering goal-functions, typology of clustering algorithms, partitioning-, hierarchicaland density based algorithms.
    14. Required learning hours and assignment
    Kontakt óra
    Félévközi készülés órákra
    Felkészülés zárthelyire
    Házi feladat elkészítése
    Kijelölt írásos tananyag elsajátítása
    Vizsgafelkészülés
    Összesen