Autor:

Kulczycki, Piotr ; Łukasik, Szymon

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Kowal, Marek - red.

Tytuł:

An algorithm for reducing the dimension and size of a sample for data exploration procedures

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, Volume 24 (2014)

Temat i słowa kluczowe:

dimension reduction ; sample size reduction ; linear transformation ; simulated annealing ; data mining

Abstract:

The paper deals with the issue of reducing the dimension and size of a data set (random sample) for exploratory data analysis procedures. The concept of the algorithm investigated here is based on linear transformation to a space of a smaller dimension, while retaining as much as possible the same distances between particular elements. ; Elements of the transformation matrix are computed using the metaheuristics of parallel fast simulated annealing. Moreover, elimination of or a decrease in importance is performed on those data set elements which have undergone a significant change in location in relation to the others. ; The presented method can have universal application in a wide range of data exploration problems, offering flexible customization, possibility of use in a dynamic data environment, and comparable or better performance with regards to the principal component analysis. Its positive features were verified in detail for the domain`s fundamental tasks of clustering, classification and detection of atypical elements (outliers).

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2014

Typ zasobu:

artykuł

DOI:

10.2478/amcs-2014-0011

Strony:

133-149

Źródło:

AMCS, volume 24, number 1 (2014) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego