Research Issues Concerning Algorithms Used For Optimizing The Data Mining Process
In this paper, we depict some of the most widely used data mining algorithms that have an overwhelming utility and influence in the research community. A data mining algorithm can be regarded as a tool that creates a data mining model. After analyzing a set of data, an algorithm searches for specific trends and patterns, then defines the parameters of the mining model based on the results of this analysis. The above defined parameters play a significant role in identifying and extracting actionable patterns and detailed statistics. The most important algorithms within this research refer to topics like clustering, classification, association analysis, statistical learning, link mining. In the following, after a brief description of each algorithm, we analyze its application potential and research issues concerning the optimization of the data mining process. After the presentation of the data mining algorithms, we will depict the most important data mining algorithms included in Microsoft and Oracle software products, useful suggestions and criteria in choosing the most recommended algorithm for solving a mentioned task, advantages offered by these software products.
Volume (Year): 4 (2010)
Issue (Month): 2 (December)
|Contact details of provider:|| Postal: |
Web page: http://www.rau.ro/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:rau:journl:v:4:y:2010:i:2:p:108-125. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alex Tabusca)
If references are entirely missing, you can add them using this form.