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

• Autorzy: Piotr Kulczycki , Szymon Łukasik
• Języki publikacji: EN

Abstrakty

EN

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).

Słowa kluczowe

EN

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

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2014
• Tom: 24
• Numer: 1
• Strony: 133-149

Daty

wydano

2014

otrzymano

2013-04-06

poprawiono

2013-11-10

Twórcy

autor

Piotr Kulczycki

• Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
• Department of Automatic Control and Information Technology, Cracow University of Technology, ul. Warszawska 24, 31-155 Cracow, Poland

autor

Szymon Łukasik

• Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
• Department of Automatic Control and Information Technology, Cracow University of Technology, ul. Warszawska 24, 31-155 Cracow, Poland

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Identyfikatory

DOI

10.2478/amcs-2014-0011