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Wyszukujesz frazę "Grzymala-Busse, J. W." wg kryterium: Autor

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    Wyświetlanie 1-3 z 3
    Tytuł:
    A new algorithm for generation of decision trees
    Autorzy:
    Grzymała-Busse, J. W.
    Hippe, Z. S.
    Knap, M.
    Mroczek, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/1965778.pdf
    Data publikacji:
    2004
    Wydawca:
    Politechnika Gdańska
    Tematy:
    artificial intelligence
    supervised machine learning
    decision trees
    Bayes networks
    Opis:
    A new algorithm for development of quasi-optimal decision trees, based on the Bayes theorem, has been created and tested. The algorithm generates a decision tree on the basis of Bayesian belief networks, created prior to the formation of the decision tree. The efficiency of this new algorithm was compared with three other known algorithms used to develop decision trees. The data set used for the experiments was a set of cases of skin lesions, histopatolgically verified.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2004, 8, 2; 243-247
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An improved comparison of three rough set approaches to missing attribute values
    Autorzy:
    Grzymala-Busse, J. W.
    Grzymala-Busse, W. J.
    Hippe, Z. S.
    Rząsa, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/969797.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    incomplete data sets
    missing attribute values
    approximations for incomplete data
    LERS data mining system
    MLEM2 algorithm
    Opis:
    In a previous paper three types of missing attribute values: lost values, attribute-concept values and "do not care" conditions were compared using six data sets. Since previous experimental results were affected by large variances due to conducting experiments on different versions of a given data set, we conducted new experiments, using the same pattern of missing attribute values for all three types of missing attribute values and for both certain and possible rules. Additionally, in our new experiments, the process of incremental replacing specified values by missing attribute values was terminated when entire rows of the data sets were full of missing attribute values. Finally, we created new, incomplete data sets by replacing the specified values starting from 5% of all attribute values, instead of 10% as in the previous experiments, with an increment of 5% instead of the previous increment of 10%. As a result, it is becoming more clear that the best approach to missing attribute values is based on lost values, with small difference between certain and possible rules, and that the worst approach is based on "do not care" conditions, certain rules. With our improved experimental setup it is also more clear that for a given data set the type of the missing attribute values should be selected individually.
    Źródło:
    Control and Cybernetics; 2010, 39, 2; 469-486
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Diagnosing skin melanoma: current versus future directions
    Autorzy:
    Hippe, Z. S.
    Bajcar, S.
    Blajdo, P.
    Grzymała-Busse, J. P.
    Grzymała-Busse, J. W.
    Knap, M.
    Paja, W.
    Wrzesień, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/1954638.pdf
    Data publikacji:
    2003
    Wydawca:
    Politechnika Gdańska
    Tematy:
    melanoma
    TDS
    machine learning in diagnosis
    Opis:
    A new database containing 410 cases of nevi pigmentosi, in four categories: benign nevus, blue nevus, suspicious nevus and melanoma malignant, carefully verified by histopathology, is described. The database is entirely different from the base presented previously, and can be readily used for research based on the so-called constructive induction in machine learning. To achieve this, the database features a different set of thirteen descriptive attributes, with a fourteenth additional attribute computed by applying values of the remaining thirteen attributes. In addition, a new program environment for the validation of computer-assisted diagnosis of melanoma, is briefly discussed. Finally, results are presented on determining optimal coefficients for the well-known ABCD formula, useful for melanoma diagnosis.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 2; 289-293
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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