VSE knjižnice (vzajemna bibliografsko-kataložna baza podatkov COBIB.SI)
  • Evolutionary design of decision trees
    Podgorelec, Vili, 1972- ; Šprogar, Matej ; Pohorec, Sandi
    Decision tree (DT) is one of the most popular symbolic machine learning approaches to classification with a wide range of applications. Decision treesare especially attractive in data mining. It has ... an intuitive representation and is, therefore, easy to understand and interpret, also by nontechnical experts. The most important and critical aspect of DTs is the process of their construction. Several induction algorithms exist that use therecursive top-down principle to divide training objects into subgroups based on different statistical measures in order to achieve homogeneous subgroups. Although being robust and fast, generally providing good results, their deterministic and heuristic nature can lead to suboptimal solutions. Therefore, alternative approaches have developed which try to overcome the drawbacks of classical induction. One of the most viable approaches seems to be the use of evolutionary algorithms, which can produce better DTs as they are searching for globally optimal solutions, evaluating potential solutions with regard to different criteria. We review the process of evolutionary design of DTs, providing the description of the most common approaches as wellas referring to recognized specializations. The overall process is first explained and later demonstrated in a step-by-step case study using a dataset from the University of California, Irvine (UCI) machine learning repository.
    Vir: Wiley interdisciplinary reviews. Data mining and knowledge discovery. - ISSN 1942-4787 (Vol. 3, iss. 2, 2013, str. 63-82)
    Vrsta gradiva - članek, sestavni del ; neleposlovje za odrasle
    Leto - 2013
    Jezik - angleški
    COBISS.SI-ID - 16733462
    DOI

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