Comparing of Results and Implemantation of Clustering Methods of Data Mining Software with a Data Set
Yükleniyor...
Dosyalar
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In data mining, the process of grouping similar data among each other in an evaluation made by the same kind of data is called clustering. Clusters are usually computed by algorithms that take advantage of relational or remote neighborhood relations to each other. A large number of clustering methods are used in practice. In this study, the differences between open source software used in data mining and results obtained by clustering methods of Oracle, Knime, Weka and RapidMiner programs are tabulated. As a source for this study, clustering analysis based article presentations by M. Turanli, U.H. Ozden and S. Turedi have been handled. For the evaluation, in 2006, economic similarities of 29 countries from candidate and member countries from the EU in terms of proprtion of inflation, Gross National Product, Internet Usage, Unemployment, Lifetime Education Indicators and Imports and Exports were tried to be clustered. Clustering operations were performed separately as 2-3-4 clusters in each program. In the clustering process, the euclidean distance is set for calculation and the number of iterations is 99 in each program. The obtained results were written in tabular form and the results were interpreted.
Açıklama
Scientific Meeting on Electric Electronics, Computer Science, Biomedical Engineerings (EBBT) -- APR 20-21, 2017 -- Istanbul Arel Univ, Istanbul, TURKEY
Temur, Gunay/0000-0002-7197-5804
WOS: 000413686600036
Temur, Gunay/0000-0002-7197-5804
WOS: 000413686600036
Anahtar Kelimeler
Kaynak
2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (Ebbt)
WoS Q Değeri
N/A
