Temat: multistage classifier - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Pattern recognition of sacroileitis with the use of multistage logic with a fuzzy loss function
Autorzy:: Burduk, R.
Powiązania:: https://bibliotekanauki.pl/articles/1965805.pdf
Data publikacji:: 2004
Wydawca:: Politechnika Gdańska
Tematy:: multistage classifier
sacroiletis
fuzzy loss function
k-nearest neighbor method
Opis:: The article describes the problem of pattern recognition of sacroileitis. Classification is based on a scheme of multistage recognition with a fuzzy loss function dependent on the node of the decision tree. Decision rules are based on k-nearest neighbors at particular internal nodes of the decision-tree. Paper presents influence of comparison fuzzy numbers on classifications results.
Źródło:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2004, 8, 2; 217-221
1428-6394
Pojawia się w:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Selection of classifier in acute abdominal pain diagnosis with decision tree model
Autorzy:: Burduk, R.
Powiązania:: https://bibliotekanauki.pl/articles/333503.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: teoria podejmowania decyzji Bayesa
wielostopniowy klasyfikator
medyczne systemy wspomagania decyzji
Bayes decision theory
multistage classifier
medical decision support systems
Opis:: The article presents the application of the decision tree classifier to the acute abdominal pain diagnosis. The recognition task model is based on a decision tree. In this model the decision tree structure is given by the experts. For the assumed structure of the decision tree the locally optimal strategy is considered. The problem discussed in the work shows a selection of different classifiers (parameters) to the internal nodes of the decision tree. Experiments conducted for selected medical diagnosis problem shows that the use of different parameters for k-NN classification can improve the quality of classification in comparison with the situation if it is used with the same parameter for all internal nodes of the decision tree.
Źródło:: Journal of Medical Informatics & Technologies; 2011, 17; 65-71
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

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