Object

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

Creator:

Kulczycki, Piotr ; Łukasik, Szymon

Date:

2014

Resource Type:

artykuł

Contributor:

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

Subtitle:

.

Group publication title:

AMCS, Volume 24 (2014)

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).

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:78921

DOI:

10.2478/amcs-2014-0011

Pages:

133-149

Source:

AMCS, volume 24, number 1 (2014) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

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