- Tytuł:
- An algorithm for reducing the dimension and size of a sample for data exploration procedures
- Autorzy:
-
Kulczycki, P.
Łukasik, S. - Powiązania:
- https://bibliotekanauki.pl/articles/330110.pdf
- Data publikacji:
- 2014
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
dimension reduction
sample size reduction
linear transformation
simulated annealing
data mining
redukcja wymiaru
transformacja liniowa
wyżarzanie symulowane
eksploracja danych - Opis:
- 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).
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2014, 24, 1; 133-149
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki