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    Wyświetlanie 1-4 z 4
    Tytuł:
    Specialized, MSE-optimal m-estimators of the rule probability especially suitable for machine learning
    Autorzy:
    Piegat, A.
    Landowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/205508.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    machine learning
    rule probability
    probability estimation
    m-estimators
    decision trees
    rough set theory
    Opis:
    The paper presents an improved sample based rule- probability estimation that is an important indicator of the rule quality and credibility in systems of machine learning. It concerns rules obtained, e.g., with the use of decision trees and rough set theory. Particular rules are frequently supported only by a small or very small number of data pieces. The rule probability is mostly investigated with the use of global estimators such as the frequency-, the Laplace-, or the m-estimator constructed for the full probability interval [0,1]. The paper shows that precision of the rule probability estimation can be considerably increased by the use of m-estimators which are specialized for the interval [phmin, phmax] given by the problem expert. The paper also presents a new interpretation of the m-estimator parameters that can be optimized in the estimators.
    Źródło:
    Control and Cybernetics; 2014, 43, 1; 133-160
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An algorithm for Bayes parameter identification with quadratic asymmetrical loss function
    Autorzy:
    Kulczycki, P.
    Mazgaj, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/970992.pdf
    Data publikacji:
    2005
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    sterowanie optymalne
    parameter identification
    Bayes decision
    quadratic asymmetrical loss function
    kernel estimators
    optimal control
    Opis:
    The paper deals with the estimation problem of model parameter values, in tasks where overestimation implies results other than underestimation, and wliere losses arising from this can be described by a quadratic function with different coefficients characterizing positive and negative errors. In the approach presented, the Bayes decision rule was used, allowing for minimizing potential losses. Calculation algorithms were based on the theory of statistical kernel estimators, which frees the method from distribution type. The result constitutes a complete numerical procedure enabling effective calculation of the value of an identified parameter or - in the multidimensional case - the vector of parameters. The method is aimed at both of the main contemporary approaches to uncertainty modeling: probabilistic and fuzzy logic. It is universal in nature and can be applied in a wide range of tasks of engineering, economy, sociology, biomedicine and other related fields.
    Źródło:
    Control and Cybernetics; 2005, 34, 4; 1127-1148
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the application of statistical kernel estimators for the demand-based design of a wireless data transmission system
    Autorzy:
    Kulczycki, P.
    Waglowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/970993.pdf
    Data publikacji:
    2005
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    telekomunikacja
    logika rozmyta
    badania operacyjne
    programowanie matematyczne
    telecommunication
    wireless broadband data transmission systems
    LMDS
    statistical kernel estimators
    fuzzy logic
    operations research
    mathematical programming
    Opis:
    The subject of this paper is the task of designing the LMDS (Local Multipoint Distribution System) wireless broadband data transmission system. The methodology of statistical kernel estimators and fuzzy logic using operations research and mathematical programming is applied to find optimal locations for its basestations. A procedure which allows to obtain such locations on the basis of potential customer distribution and their expected demand, also in the cases of uncertain and non-stationary data, is investigated.
    Źródło:
    Control and Cybernetics; 2005, 34, 4; 1149-1167
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayes classification of imprecise information of interval type
    Autorzy:
    Kulczycki, P.
    Kowalski, P. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/205655.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    data analysis
    classification
    imprecise information
    interval type information
    statistical kernel estimators
    reduction in pattern size
    classifier parameter correction
    sensitivity method for artificial neural networks
    Opis:
    The subject of the investigation presented here is Bayes classification of imprecise multidimensional information of interval type by means of patterns defined through precise data, e.g. deterministic or sharp. For this purpose the statistical kernel estimators methodology was applied, which makes the resulting algorithm independent of the pattern shape. In addition, elements of pattern sets which have insignificant or negative influence on the correctness of classification are eliminated. The concept for realizing the procedure is based on the sensitivity method, used in the domain of artificial neural networks. As a result of this procedure the number of correct classifications and - above all - calculation speed increased significantly. A further growth in quality of classification was achieved with an algorithm for the correction of classifier parameter values. The results of numerical verification, carried out on pseudorandom and benchmark data, as well as a comparative analysis with other methods of similar conditioning, have validated the concept presented here and its positive features.
    Źródło:
    Control and Cybernetics; 2011, 40, 1; 101-123
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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