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ID 28425
file
B1005.pdf 292 KB
creator
Minegishi, Tatsuya
Ise, Masayuki
Niimi, Ayahiko
Konishi, Osamu
NDC
Technology. Engineering
abstract
Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the data correspond to data stream is data stream mining. In this paper, we propose the feature selection with online decision tree. At first, we construct online type decision tree to regard credit card transaction data as data stream on data stream mining. At second, we select attributes thought to be important for detection of illegal use. We apply VFDT (Very Fast Decision Tree learner) algorithm to online type decision tree construction.
journal title
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
start page
208
end page
212
date of issued
2009-11
publisher
IEEE SMC Hiroshima Chapter
issn
1883-3977
language
eng
nii type
Conference Paper
HU type
Conference Papers
DCMI type
text
format
application/pdf
text version
publisher
rights
(c) Copyright by IEEE SMC Hiroshima Chapter.
relation url
department
Graduate School of Engineering