SVM Feature Selection Based Rotation Forest Ensemble Classifiers to Improve Computer-Aided Diagnosis of Parkinson Disease.

Detalles Bibliográficos
Publicado en:Journal of Medical Systems Vol. 36; no. 4; pp. 2141 - 2148
Autor principal: Ozcift, Akin
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Aug2012
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=117144077&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 117144077
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01485598
        4N0
      jtl: Journal of Medical Systems
      issn: 01485598
      maglogo: N
    pubinfo:
      dt: Aug2012
      vid: 36
      iid: 4
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        117144077
        117144077
        117144077
        10.1007/s10916-011-9678-1
        117144077
      ppf: 2141
      ppct: 7
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: SVM Feature Selection Based Rotation Forest Ensemble Classifiers to Improve Computer-Aided Diagnosis of Parkinson Disease.
      aug:
        au: Ozcift, Akin
        affil: Gaziantep Vocational School of Higher Education, Computer Programming Division, University of Gaziantep, Gaziantep Turkey
      sug:
        subj:
          Diagnosis, Computer Assisted
          Parkinson Disease Diagnosis
          Classification
          Human
          Breast Neoplasms
          Diabetes Mellitus
          ROC Curve
          kappa Statistic
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N