Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Powiadomienia systemowe

Sesja wygasła!
Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: clustering of variables

Sortuj według:

Ogranicz wyniki do:

On the clustering of correlated random variables

Gniazdowski Z., Kaliszewski D.

Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki

2018

nr 18

45--114

In this work, the possibility of clustering correlated random variables was examined, both because of their mutual similarity and because of their similarity to the principal components. The k-means algorithm and spectral algorithms were used for clustering. For spectral methods, the similarity matrix was both the matrix of relation established on the level of correlation and the matrix of coefﬁcients of determination. For four different sets of data, different ways of measuring the disimilarity of variables were analyzed, and the impact of the diversity of initial points on the efﬁciency of the k-means algorithm was analyzed.

New Interpretation of Principal Components Analysis

Gniazdowski Z.

Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki

2017

nr 16

43--65

A new look on the principal component analysis has been presented. Firstly,ageometric interpretation of determination coefﬁcient was shown. In turn, the ability to represent the analyzed data and their interdependencies in the form of easy-tounderstand basic geometric structures was shown. As a result of the analysis of these structures it was proposed to enrich the classical PCA. In particular, it was proposed a new criterion for the selection of important principal components and a new algorithm for clustering primary variables by their level of similarity to the principal components. Virtual and real data spaces, as well as tensor operations on data, have also been identiﬁed.The anisotropy of the data was identiﬁed too.