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Wyszukujesz frazę "classifier design" wg kryterium: Temat

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    Wyświetlanie 1-6 z 6
    Tytuł:
    Iteratively reweighted least squares classifier and its l2- and l1-regularized Kernel versions
    Autorzy:
    Łęski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/199904.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    classifier design
    IRLS
    conjugate gradient optimization
    gradient projection
    Kernel matrix
    Opis:
    This paper introduces a new classifier design method based on regularized iteratively reweighted least squares criterion function. The proposed method uses various approximations of misclassification error, including: linear, sigmoidal, Huber and logarithmic. Using the represented theorem a kernel version of classifier design method is introduced. The conjugate gradient algorithm is used to minimize the proposed criterion function. Furthermore, .1-regularized kernel version of the classifier is introduced. In this case, the gradient projection is used to optimize the criterion function. Finally, an extensive experimental analysis on 14 benchmark datasets is given to demonstrate the validity of the introduced methods.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2010, 58, 1; 171-182
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Fuzzy If-Then Rule-Based Nonlinear Classifier
    Autorzy:
    Łęski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/908190.pdf
    Data publikacji:
    2003
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    informatyka
    classifier design
    fuzzy if-then rules
    generalization control
    mixture of experts
    Opis:
    This paper introduces a new classifier design method that is based on a modification of the classical Ho-Kashyap procedure. The proposed method uses the absolute error, rather than the squared error, to design a linear classifier. Additionally, easy control of the generalization ability and robustness to outliers are obtained. Next, an extension to a nonlinear classifier by the mixture-of-experts technique is presented. Each expert is represented by a fuzzy if-then rule in the Takagi-Sugeno-Kang form. Finally, examples are given to demonstrate the validity of the introduced method.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2003, 13, 2; 215-223
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Kernel Ho-Kashyap classifier with generalization control
    Autorzy:
    Łęski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/907269.pdf
    Data publikacji:
    2004
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    metoda jądrowa
    metoda odporna
    projekt klasyfikatora
    kernel methods
    classifier design
    Ho-Kashyap classifier
    generalization control
    robust methods
    Opis:
    This paper introduces a new classifier design method based on a kernel extension of the classical Ho-Kashyap procedure. The proposed method uses an approximation of the absolute error rather than the squared error to design a classifier, which leads to robustness against outliers and a better approximation of the misclassification error. Additionally, easy control of the generalization ability is obtained using the structural risk minimization induction principle from statistical learning theory. Finally, examples are given to demonstrate the validity of the introduced method.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2004, 14, 1; 53-61
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Membership function - ARTMAP neural networks
    Autorzy:
    Sinčák, P.
    Hric, M.
    Vaščák, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/1931570.pdf
    Data publikacji:
    2003
    Wydawca:
    Politechnika Gdańska
    Tematy:
    pattern recognition principles
    classifier design
    classification accuracy assessment
    contingency tables
    backpropagation neural networks
    fuzzy BP neural networks
    ART and ARTMAP neural networks
    modular neural networks
    neural networks
    Opis:
    The project deals with the application of computational intelligence (CI) tools for multispectral image classification. Pattern Recognition scheme is a global approach where the classification part is playing an important role to achieve the highest classification accuracy. Multispectral images are data mainly used in remote sensing and this kind of classification is very difficult to assess the accuracy of classification results. There is a feedback problem in adjusting the parts of pattern recognition scheme. Precise classification accuracy assessment is almost impossible to obtain, being an extremely laborious procedure. The paper presents simple neural networks for multispectral image classification, ARTMAP-like neural networks as more sophisticated tools for classification, and a modular approach to achieve the highest classification accuracy of multispectral images. There is a strong link to advances in computer technology, which gives much better conditions for modelling more sophisticated classifiers for multispectral images.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 1; 43-52
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Coupled fuzzy logic and experimental design application for simulation of a coal classifier in an industrial environment
    Autorzy:
    Khoshdast, Hamid
    Soflaeian, Ali
    Shojaei, Vahideh
    Powiązania:
    https://bibliotekanauki.pl/articles/109838.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    combined modeling
    fuzzy logic
    experimental design
    coal classifier
    industry
    Opis:
    Design of experiments (DOE) is an effective method providing useful information about the interaction of operating variables and the way the total system works by using statistical analyses. However, its industrial application is limited because it is almost difficult to maintain variables in DOE matrix at desired constant levels in industrial environment. Thus, this paper aims to present a new mixed modeling method which is a combination of fuzzy logic and design of experiments methods to overcome such practical limitations. The method first uses a fuzzy model which is trained by practical data gathered from industry to predict DOE response corresponding to each run in DOE matrix. Then, a statistical parametric model is constructed for the prediction of process response to any change of operating parameters under real industrial conditions. The proposed mixed method was successfully validated by using data obtained from a coal hydraulic classifier at Zarand Coal Washing Plant (Kerman, Iran). The method also seems to be a promising tool for modeling all devices and processes in real industrial environment and allows researchers to benefit from all the advantages of experimental design and fuzzy logic methods simultaneously.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2019, 55, 2; 504-515
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Combining classifiers - concept and applications
    Autorzy:
    Woźniak, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/333902.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    łączenie klasyfikatorów
    systemy wielo-klasyfikatorów
    rozpoznawanie obrazów
    projekt nagrzewnicy
    projekt zespołu
    combining classifier
    multiple classifier systems
    pattern recognition
    fuser design
    ensemble design
    Opis:
    Problem of pattern recognition is accompanying our whole life, therefore methods of automatic pattern recognition is one of the main trend in Artificial Intelligence. Multiple classifier systems (MCSs) are currently the focus of intense research. In this conceptual approach, the main effort is concentrated on combining knowledge of the set of individual classifiers. Proposed work presents a brief survey of the main issues connected with MCSs and provides comparative analysis of some classifier fusion methods.
    Źródło:
    Journal of Medical Informatics & Technologies; 2010, 15; 19-27
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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