Técnicas de clasificación y análisis de representacion del conocimiento para problemas de diagnóstico


Authors

  • Guillermo Roberto Solarte Martinez
  • Carlos Alberto Ocampo

DOI:

https://doi.org/10.22517/23447214.2639

Abstract

El diagnostico medico es un proceso fundamental para la identificación de enfermedades, por eso en esta investigación se analizan algunas metodologías de clasificación de datos basados en patrones como son los arboles de decisiones, clúster y Análisis de componentes principales, estas técnicas de clasificación nos ayudan a la toma decisiones de una manera más eficiente y temprana.

Downloads

Download data is not yet available.

Downloads

Published

2009-08-30

How to Cite

Solarte Martinez, G. R., & Ocampo, C. A. (2009). Técnicas de clasificación y análisis de representacion del conocimiento para problemas de diagnóstico. Scientia Et Technica, 2(42). https://doi.org/10.22517/23447214.2639

Issue

Vol. 2 No. 42 (2009)

Section

Sistemas y Computación

License

Copyrights

The journal is free open access. The papers are published under the Creative Commons Attribution / Attribution-NonCommercial-NoDerivatives 4.0 International - CC BY-NC-ND 4.0 license. For this reason, the author or authors of a manuscript accepted for publication will yield all the economic rights to the Universidad Tecnológica of Pereira free of charge, taking into account the following:

In the event that the submitted manuscript is accepted for publication, the authors must grant permission to the journal, in unlimited time, to reproduce, to edit, distribute, exhibit and publish anywhere, either by means printed, electronic, databases, repositories, optical discs, Internet or any other required medium. In all cases, the journal preserves the obligation to respect, the moral rights of the authors, contained in article 30 of Law 23 of 1982 of the Government Colombian.

The transferors using ASSIGNMENT OF PATRIMONIAL RIGHTS letter declare that all the material that is part of the article is entirely free of copyright.  Therefore, the authors are responsible for any litigation or related claim to intellectual property rights. They exonerate of all responsibility to the Universidad Tecnológica of Pereira (publishing entity) and the Scientia et Technica journal. Likewise, the authors accept that the work presented will be distributed in free open access, safeguarding copyright under the Creative Commons Attribution / Recognition-NonCommercial-NoDerivatives 4.0 International - https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es license.