MANAGING LARGE COLLECTIONS OF DATA MINING MODELS.

This article provides information on managing large collections of data mining models for data analysts. Discussed is the traditional method of aggregating the data into large segments, then using domain knowledge combined with "intelligent" model-building methods to produce models. In this study re...

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Detalles Bibliográficos
Publicado en:Communications of the ACM Vol. 51; no. 2; pp. 85 - 90
Autores principales: Bing Liu, Tuzhilin, Alexander
Formato: Artículo
Publicado: Association for Computing Machinery Feb2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2008
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          Bing Liu
          Tuzhilin, Alexander
        affil:
          Professor, Department of Computer Science, University of Illinois, Chicago.
          Professor of information systems and NEC Faculty Fellow, Information, Operations & Management Sciences Department, Leonard N. Stern School of Business, New York University, New York.
      su:
        Data mining
        Data modeling
        Computer simulation
        Data analysis
        Software engineering
        Model-integrated computing
      sug:
        subj:
          Data mining
          Data modeling
          Computer simulation
          Data analysis
          Software engineering
          Model-integrated computing
      ab: This article provides information on managing large collections of data mining models for data analysts. Discussed is the traditional method of aggregating the data into large segments, then using domain knowledge combined with "intelligent" model-building methods to produce models. In this study researchers want to make the argument that a generic model-management system is needed to facilitate large-scale model building applications. The researchers also want to identify the main issues and problems of model management and set up a research agenda.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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          year: 2008
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