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Raport Badawczy = Research Report ; RB/78/2011
Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences
527-551 stron ; 21 cm ; Bibliografia s. 550-551
In this paper we introduce a hybrid approach to data series classification. The approach is based on the concept of aggregated upper and lower envelopes, and the principal components here called ‘essential attributes’, generated by multilayer neural networks. The essential attributes are represented by outputs of hidden layer neurons. Next, the real valued essential attributes are nominalized and symbolic data series representation is obtained. The symbolic representation is used to generate decision rules in the IF. . .THEN. . . form for data series classification. The approach reduces the dimension of data series. The efficiency of the approach was verified by considering numerical examples.
Raport Badawczy = Research Report
Licencja Creative Commons Uznanie autorstwa 4.0
Zasób chroniony prawem autorskim. [CC BY 4.0 Międzynarodowe] Korzystanie dozwolone zgodnie z licencją Creative Commons Uznanie autorstwa 4.0, której pełne postanowienia dostępne są pod adresem: ; -
Instytut Badań Systemowych Polskiej Akademii Nauk
Biblioteka Instytutu Badań Systemowych PAN
Oct 19, 2021
Oct 19, 2021
43
https://rcin.org.pl./publication/255072
Edition name | Date |
---|---|
RB-2011-78 : Krawczak Maciej, Szkatuła Grażyna Maria : A hybrid approach to dimension reduction in classification | Oct 19, 2021 |
Krawczak, Maciej Szkatuła, Grażyna
Krawczak, Maciej Szkatuła, Grażyna
Krawczak, Maciej Szkatuła, Grażyna