A Complete Algorithm for the Reduction of Pattern Data in the Classification of Interval Information
PBN-AR
Instytucja
Instytut Badań Systemowych Polskiej Akademii Nauk
Informacje podstawowe
Główny język publikacji
angielski
Czasopismo
International Journal of Computational Methods
ISSN
0219-8762
EISSN
1793-6969
Wydawca
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI
URL
Rok publikacji
2016
Numer zeszytu
3
Strony od-do
1650018-1-1650018-26
Numer tomu
13
Link do pełnego tekstu
Identyfikator DOI
Liczba arkuszy
1,1
Autorzy
(liczba autorów: 2)
Pozostali autorzy
+ 1
Słowa kluczowe
angielski
data sample reduction
sensitivity method for artificial neural networks
data analysis
classification of imprecise information
interval data
Streszczenia
Język
angielski
Treść
The aim of this paper is to present a novel method of data sample reduction that can be applied, in particular, to the classification of interval type imprecise information. Its concept is based on the sensitivity method, inspired by artificial neural networks, while the goal is to increase the number of apposite classifications, and, consequently, to increase calculation speed. As evident in this paper, the use of reduction algorithm eliminates the particular elements of all data sample patterns which have insignificant or negative influence on the correctness of classification. The methodology was tested on pseudo-random and real data, as well as by way of comparative analysis with similar task algorithms. The presented procedure was also tested for use in situations in which the data sample representing the individual classes had been obtained by the k-means clustering procedure.
Cechy publikacji
original-article
Inne
System-identifier
27052
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