• DocumentCode
    2336126
  • 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
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    671
  • Lastpage
    672
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-7695-1119-8
  • Type

    conf

  • DOI
    10.1109/ICDM.2001.989602
  • Filename
    989602