Title :
Mining California vital statistics data
Author :
Du Zhang ; Ha, Quoc Luan ; Lu, Meiliu
Author_Institution :
Dept. of Comput. Sci., California State Univ., Sacramento, CA, USA
Abstract :
Vital statistics data offer a fertile ground for data mining. The authors discuss the results of a data mining project on the causes of death aspect of the vital statistics data in the state of California. A data mining tool called Cubist is used to build predictive models out of two million cases over a nine-year period. The objective of our study is to discover knowledge that can be used to gain insight into various aspects of mortality in California, to predict health issues related to the causes of death, to offer an aid to decision- or policy-making processes, and to provide useful information services to the customers. The results obtained in our study contain valuable new information
Keywords :
data mining; demography; government data processing; health care; social sciences computing; statistical analysis; very large databases; California vital statistics data mining; Cubist; causes of death; data mining project; data mining tool; decision-making process; health issues; information services; knowledge discovery; policy-making process; Cleaning; Computer science; Data mining; Data preprocessing; Information resources; Monitoring; Predictive models; Public healthcare; Statistics; Testing;
Conference_Titel :
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1119-8
DOI :
10.1109/ICDM.2001.989602
