ePrints.FRI - University of Ljubljana, Faculty of Computer and Information Science

Learning optimal decisions with classification trees

Minja Zorc (2009) Learning optimal decisions with classification trees. EngD thesis.

[img] PDF
Download (1642Kb)


    Learning classification and regression models is one of the most important subfields of machine learning. Classification and regression models are constructed from learning set and used to classify new examples. In practice, we would often need model, which proposes optimal decision, for instance the best therapy for a certain type of illness for a particular patient. The main aim of the diploma thesis is to adapt the algorithm for the construction of classification trees to construct trees that would not predict the outcome but rather the decision leading to the desired outcome. Besides that, we had to develop the methods for measuring the quality of such models, and use it to test them on synthetic and real-world data sets.

    Item Type: Thesis (EngD thesis)
    Keywords: machine learning, classification tree, attribute selection measure, optimal therapy
    Number of Pages: 39
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Janez Demšar257Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=7149396)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 860
    Date Deposited: 08 Jun 2009 08:29
    Last Modified: 13 Aug 2011 00:35
    URI: http://eprints.fri.uni-lj.si/id/eprint/860

    Actions (login required)

    View Item