Literature DB >> 1482916

Combining logistic regression and neural networks to create predictive models.

K A Spackman1.   

Abstract

Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building with neural networks.

Mesh:

Year:  1992        PMID: 1482916      PMCID: PMC2248116     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN: 0195-4210


  2 in total

1.  Estimation of the probability of an event as a function of several independent variables.

Authors:  S H Walker; D B Duncan
Journal:  Biometrika       Date:  1967-06       Impact factor: 2.445

Review 2.  Clinical prediction rules. Applications and methodological standards.

Authors:  J H Wasson; H C Sox; R K Neff; L Goldman
Journal:  N Engl J Med       Date:  1985-09-26       Impact factor: 91.245

  2 in total

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