Please use this identifier to cite or link to this item:
|Title:||Exploration mining in diabetic patients databases: Findings and conclusions|
|Authors:||Hsu, W. |
|Citation:||Hsu, W.,Lee, M.L.,Liu, B.,Ling, T.W. (2000). Exploration mining in diabetic patients databases: Findings and conclusions. Proceeding of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining : 430-436. ScholarBank@NUS Repository.|
|Abstract:||Real-life data mining applications are interesting because they often present a different set of problems for data miners. One such real-life application that we have done is on the diabetic patients databases. Valuable lessons are learnt from this application. In particular, we discover that the often neglected pre-processing and post-processing steps in knowledge discovery are the most critical elements in determining the success of a real-life data mining application. In this paper, we shall discuss how we carry out knowledge discovery on this diabetic patient database, the interesting issues that have surfaced, as well as the lessons we have learnt from this application. We will describe a semi-automatic means for cleaning the diabetic patient database, and present a step-by-step approach to help the health doctors explore their data and to understand the discovered rules better.|
|Source Title:||Proceeding of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 22, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.