|
|
|
Contact Us||
About Us
. |
|
|
 |
|
|
|
|
|

September 2012 Vol. 1(6)
• Abstract
•
Full text
•Reprint
(PDF) ( 152 KB)
Search
Pubmed for articles by:
Ogwueleka FN
Okeke GN
Other links:
PubMed Citation
Related articles in PubMed |
|
Global Advanced Research Journal of
Engineering, Technology and Innovation (GARJETI) ISSN:
2315-5124
September 2012 Vol. 1(6), pp 131-137
Copyright © 2012 Global Advanced Research Journals
Full Length Research Paper
|
Methodology and
tool selection criteria in data mining
Ogwueleka, Francisca Nonyelum and Okeke, Georgina
Nkolika
Department of Computer Science, Federal University
of Technology, Minna, Niger State.
Email: nonnyraymond@yahoo.co.uk
Corresponding author Email:
nonnyraymond@yahoo.co.uk
Accepted 20 August 2012
|
|
Abstract |
|
The application of data mining algorithms requires
the use of powerful software tools. Data mining and
decision support software is expensive and selection
of the wrong tools can be costly both in terms of
wasted money and time lost. One of the most
difficult tasks in the whole data mining process is
to choose the right data mining tool (software), as
data mining is evolving and maturing and many
organizations are incorporating this technology into
their business practices; the number of available
tools continues to grow, the selection of the most
suitable tool becomes increasingly difficult. This
paper proposes a methodology for selecting the best
among the assortment of commercially available data
mining software tools.
Keywords:
Data mining, algorithm, methodology, data mining
tools, knowledge discovery
|
| |
|
|
|