Diabetes Data Analysis and Prediction Model Discovery Using RapidMiner

被引：0

作者：

Han, Jianchao ^{[1
]}

Rodriguze, Juan C. ^{[1
]}

Beheshti, Mohsen ^{[1
]}

机构：

[1] Calif Statement Univ Dominguez Hills, Dept Comp Sci, Carson, CA USA

来源：

FGCN: PROCEEDINGS OF THE 2008 SECOND INTERNATIONAL CONFERENCE ON FUTURE GENERATION COMMUNICATION AND NETWORKING, VOLS 1 AND 2 | 2008年

关键词：

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Data mining techniques have been extensively applied in bioinformatics to analyze biomedical data. In this paper, we choose the Rapid-I's RapidMiner as our tool to analyze a Pima Indians Diabetes Data Set, which collects the information of patients with and without developing diabetes. The discussion follows the data mining process. The focus will be on the data preprocessing, including attribute identification and selection, outlier removal, data normalization and numerical discretization, visual data analysis, hidden relationships discovery, and a diabetes prediction model construction.

引用

页码：1048 / 1051

页数：4

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