A Data Preparation Methodology in Data Mining Applied to Mortality Population Databases.
It is known that the data preparation phase is the most time consuming in the data mining process, using up to 50 % or up to 70 % of the total project time. Currently, data mining methodologies are of general purpose and one of their limitations is that they do not provide a guide about what particu...
| Publicado en: | Journal of Medical Systems Vol. 39; no. 11; pp. 1 - 7 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Nov2015
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925189&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925189 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Nov2015 vid: 39 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925189 115925189 115925189 10.1007/s10916-015-0312-5 115925189 ppf: 1 ppct: 6 formats: fmt: @attributes: type: P tig: atl: A Data Preparation Methodology in Data Mining Applied to Mortality Population Databases. aug: au: Pérez, Joaquín Iturbide, Emmanuel Olivares, Víctor Hidalgo, Miguel Martínez, Alicia Almanza, Nelva affil: Tecnológico Nacional de México / CENIDET, Interior Internado Palmira s/n, Palmira, 62490 Cuernavaca Mexico sug: subj: Resource Databases, Health Mortality Mexico Data Mining Mexico Human Cause of Death Geographic Locations ab: It is known that the data preparation phase is the most time consuming in the data mining process, using up to 50 % or up to 70 % of the total project time. Currently, data mining methodologies are of general purpose and one of their limitations is that they do not provide a guide about what particular task to develop in a specific domain. This paper shows a new data preparation methodology oriented to the epidemiological domain in which we have identified two sets of tasks: General Data Preparation and Specific Data Preparation. For both sets, the Cross-Industry Standard Process for Data Mining (CRISP-DM) is adopted as a guideline. The main contribution of our methodology is fourteen specialized tasks concerning such domain. To validate the proposed methodology, we developed a data mining system and the entire process was applied to real mortality databases. The results were encouraging because it was observed that the use of the methodology reduced some of the time consuming tasks and the data mining system showed findings of unknown and potentially useful patterns for the public health services in Mexico. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|